Journal articles: 'Avoidance Map'

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Yuan, Rupeng, Fuhai Zhang, Jiadi Qu, Guozhi Li, and Yili Fu. "A novel obstacle avoidance method based on multi-information inflation map." Industrial Robot: the international journal of robotics research and application 47, no. 2 (August 24, 2019): 253–65. http://dx.doi.org/10.1108/ir-05-2019-0114.

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Purpose This paper aims to provide a novel obstacle avoidance method based on multi-information inflation map. Design/methodology/approach In this paper, the multi-information inflation map is introduced, which considers different information, including a two-dimensional grid map and a variety of sensor information. The static layer of the map is pre-processed at first. Then sensor inputs are added in different semantic layers. The processed information in semantic layers is used to update the static layer. The obstacle avoidance algorithm based on the multi-information inflation map is able to generate different avoidance paths for different kinds of obstacles, and the motion planning based on multi-information inflation map can track the global path and drive the robot. Findings The proposed method was implemented on a self-made mobile robot. Four experiments are conducted to verify the advantages of the proposed method. The first experiment is to demonstrate the advantages of the multi-information inflation map over the layered cost map. The second and third experiments verify the effectiveness of the obstacle avoidance path generation and motion planning. The fourth experiment comprehensively verifies that the obstacle avoidance algorithm is able to deal with different kinds of obstacles. Originality/value The multi-information inflation map proposed in this paper has better performance than the layered cost maps. As the static layer is pre-processed, the computational efficiency is higher. Sensor information is added in semantic layers with different cost attenuation coefficients. All layers are reset before next update. Therefore, the previous state will not affect the current situation. The obstacle avoidance and motion planning algorithm based on the multi-information inflation map can generate different paths for different obstacles and drive a robot safely and control the velocity according to different conditions.

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Patry, G., K. Jarvi, E. D. Grober, K. C. Lo, and L. Spencer. "Map: micro-testicular sperm extraction avoidance program." Fertility and Sterility 90 (September 2008): S98. http://dx.doi.org/10.1016/j.fertnstert.2008.07.1063.

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Fang, Cheng, and Xilun Ding. "A Global Obstacle-Avoidance Map for Anthropomorphic Arms." International Journal of Advanced Robotic Systems 11, no. 7 (January 2014): 117. http://dx.doi.org/10.5772/58724.

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Monsieurs, P., K. Coninx, and E. Flerackers. "Collision avoidance and map construction using synthetic vision." Virtual Reality 5, no. 2 (June 2000): 72–81. http://dx.doi.org/10.1007/bf01424338.

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An, Jiping, Xinhong Li, Zhibin Zhang, Guohui Zhang, Wanxin Man, Gangxuan Hu, and Junwei He. "Path Planning for Self-Collision Avoidance of Space Modular Self-Reconfigurable Satellites." Aerospace 9, no. 3 (March 5, 2022): 141. http://dx.doi.org/10.3390/aerospace9030141.

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Space modular self-reconfigurable satellite (SMSRS) is a new type of satellite. The research on self-collision avoidance of SMSRS is important for its on-orbit safety but is not completely solved. This paper offers a new method for joint path planning for self-collision avoidance of SMSRS. Firstly, we establish the collision detection model for SMSRS based on forward kinematics and the spherical nonholonomic envelope to detect the collision occurring in SMSRS. Then, to achieve offline path planning in joint space, we proposed the self-collision avoidance strategy, which splices multiple C-spaces based on the pre-defined joint path into a binary map, and then transforms the binary map into a map with the dangerous potential field, and planning algorithms based on a map with the dangerous potential field is proposed to find the optimal collision-free path. The new method is applied to two cases and both find collision-free joint paths for SMSRS successfully, which demonstrates the feasibility of the method. In addition, this study bridges the gap in the study of self-collision avoidance of super-redundant self-reconfigurable satellites.

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Gao, Zan, Leslie William Podlog, and Louis Harrison. "College Students’ Goal Orientations, Situational Motivation and Effort/Persistence in Physical Activity Classes." Journal of Teaching in Physical Education 31, no. 3 (July 2012): 246–60. http://dx.doi.org/10.1123/jtpe.31.3.246.

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The purpose of this study was to examine relationships among college students’ 2 × 2 goal orientations (mastery-approach [MAp], mastery-avoidance [MAv], performance-approach [PAp], performance-avoidance [PAv]), situational motivation (intrinsic motivation, identified regulation, external regulation and amotivation) and effort/persistence in physical activity classes. Participants (140 female, 109 male) completed a battery of questionnaires assessing the outcome variables at the last week of instruction. Regression analyses revealed that MAp and PAp emerged as positive predictors for intrinsic motivation whereas MAp was the only positive predictor for identified regulation. MAp was negatively related to amotivation (AM), while PAp and PAv were positively related to AM. In addition, MAp, PAp, intrinsic motivation, and identified regulation were significant positive predictors of effort/persistence.

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Li, Jingmin. "Path Planning of Industrial Wheeled Robots Based on Wireless Communication and Machine Learning Algorithms." Mobile Information Systems 2022 (March 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/3386116.

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With the advancement of science and technology, robotics has made considerable progress. Robots can free humans from heavy repetitive labor. From the industrial field to the lives of the general public, robots are playing an increasingly important role. Path planning is one of the core contents of industrial wheeled robotics and has very important significance. Based on the reinforcement Q learning and BP network, this work studies the path planning of industrial wheeled robots. According to task requirements of path planning, design learning strategies, and control rules, use wireless communication to transmit environmental perception information and propose corresponding control strategies. The main researches are as follows: (1) Based on grid map environment, a path planning algorithm with Q-CM learning is designed. The algorithm first designs robot states and actions based on reinforcement Q learning and grid map and establishes Q matrix. Secondly, a coordinate matching (CM) obstacle avoidance control rule is designed to improve the efficiency of robot avoidance. Then, a reward function is designed for the evaluation problem of action execution. (2) Based on the map environment of free space and the generalization ability of BP neural network, a robot path planning with Q-BP learning is designed. The algorithm first designs the sensor detection mechanism and action selection strategy according to the state of the robot in the map environment. Secondly, a dynamic reward function is designed. Then, according to the obstacle avoidance requirements of special obstacles, the obstacle avoidance rules after three shocks were designed. The experimental results show robots can perform better path planning in a discrete and continuous free space map, and the obstacle avoidance effect is good.

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Kobayashi, Yuichi, and Takahiro Nomura. "Learning of Obstacle Avoidance with Redundant Manipulator by Hierarchical SOM." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 5 (July 20, 2011): 525–31. http://dx.doi.org/10.20965/jaciii.2011.p0525.

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This paper proposes a method of obstacle avoidance motion generation for a redundant manipulator with a Self-OrganizingMap (SOM) and reinforcement learning. To consider redundancy, two types of SOMs - a hand position map and a joint angle map - are combined. Multiple joint angles corresponding to the same hand position are memorized in the proposed map. Preserved redundant configuration information is used to generate motions based on tasks and situations, while resolving inverse kinematics problems with a redundant manipulator. The proposed map is applied to planning motion control using reinforcement learning in an unknown environment, where collision with obstacles is detected only directly by tactile sensing. The feasibility of the proposed framework was verified by simulation and experiments with an arm robot with force and a vision sensors.

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Gowri R. and Rathipriya R. "Local Optima Avoidance in GA Biclustering using Map Reduce." International Journal of Knowledge Discovery in Bioinformatics 6, no. 1 (January 2016): 37–47. http://dx.doi.org/10.4018/ijkdb.2016010104.

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One of the prominent issues in Genetic Algorithm (GA) is premature convergence on local optima. This restricts the enhanced optimal solution searching in the entire search space. Population size is one of the influencing factors in Genetic Algorithm. Increasing the population size will improvise the randomized searching and maintains the diversity in the population. It also increases its computational complexity. Especially in GA Biclustering (GABiC), the search should be randomized to find more optimal patterns. In this paper, a novel approach for population setup in MapReduce framework is proposed. The maximal population is split into population sets, and these groups will proceed searching in parallel using MapReduce framework. This approach is attempted for biclustering the gene expression dataset in this paper. The performance of this proposed work seems promising on comparing its results with those obtained from previous hybridized optimization approaches. This approach will also handle data scalability issues and applicable to the big data biclustering problems.

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Krasuski, Adam, and Michał Meina. "Correcting Inertial Dead Reckoning Location Using Collision Avoidance Velocity-Based Map Matching." Applied Sciences 8, no. 10 (October 6, 2018): 1830. http://dx.doi.org/10.3390/app8101830.

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We propose an algorithm for map-aided inertial dead reckoning (DR) for indoor navigation. The technique is based on a concept of collision avoidance velocity. New positions estimated by DR are checked for collision detection with walls and if such a situation is detected, the collision avoidance velocity is calculated to avert the obstacles. The differences between an individual’s indicated velocity and collision avoidance velocity are then used to correct errors for further path development. The best performance of the proposed technique is achieved when the individual moves along building obstacles. This type of movement is typical for firefighters, during search and rescue operations in thick smoke. Such conditions provided the environment for testing our algorithm.

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Liu, Li-sang, Jia-feng Lin, Jin-xin Yao, Dong-wei He, Ji-shi Zheng, Jing Huang, and Peng Shi. "Path Planning for Smart Car Based on Dijkstra Algorithm and Dynamic Window Approach." Wireless Communications and Mobile Computing 2021 (February 15, 2021): 1–12. http://dx.doi.org/10.1155/2021/8881684.

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Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

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van de Merwe, G. K., S. C. Mallam, Ø. Engelhardtsen, and S. Nazir. "Exploring navigator roles and tasks in transitioning towards supervisory control of autonomous collision avoidance systems." Journal of Physics: Conference Series 2311, no. 1 (July 1, 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2311/1/012017.

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Abstract This study aims to systematically map and assess performance requirements for collision avoidance manoeuvring for two cases. A case where the navigator performs collision avoidance, and a case where collision avoidance is performed by collision avoidance system where the navigator acts as its supervisor. An appraisal of collision avoidance manoeuvring was performed based on three data sources: the collision avoidance regulations, a ferry operator’s procedures, and interviews with navigators including in situ observations. A framework was established in which the gathered data was structured and analysed using a cognitive task analysis approach. Based on the results, performance requirements and information needs were established. Further work will focus on detailing the navigator’s information needs and the corresponding system’s transparency requirements to support effective human performance.

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Chen, Lin, Yongting Zhao, Huanjun Zhao, and Bin Zheng. "Non-Communication Decentralized Multi-Robot Collision Avoidance in Grid Map Workspace with Double Deep Q-Network." Sensors 21, no. 3 (January 27, 2021): 841. http://dx.doi.org/10.3390/s21030841.

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This paper presents a novel decentralized multi-robot collision avoidance method with deep reinforcement learning, which is not only suitable for the large-scale grid map workspace multi-robot system, but also directly processes Lidar signals instead of communicating between the robots. According to the particularity of the workspace, we handcrafted a reward function, which considers both the collision avoidance among the robots and as little as possible change of direction of the robots during driving. Using Double Deep Q-Network (DDQN), the policy was trained in the simulation grid map workspace. By designing experiments, we demonstrated that the learned policy can guide the robot well to effectively travel from the initial position to the goal position in the grid map workspace and to avoid collisions with others while driving.

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Kim, Jonghoek. "Path-Following and Collision-Avoidance Controls of a Robot in a Large Building with One or More Elevators." Applied Sciences 13, no. 17 (August 27, 2023): 9691. http://dx.doi.org/10.3390/app13179691.

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For planning a robot’s path inside a large building with one or more elevators, we develop a topological map, called the building Voronoi graph. Using the building Voronoi graph, the robot finds the shortest path to the goal and follows the path. In the case where the robot detects an object with arbitrary shapes (e.g., human) while following the path, the robot avoids the object utilizing reactive control laws. The proposed reactive collision-avoidance control is unique in considering collision avoidance with map environments as well as (moving or static) objects having arbitrary shapes. As far as we know, our paper is novel in addressing how to make the robot follow the building Voronoi graph, while avoiding collision with map environments as well as objects with arbitrary shapes.

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Zou, Ying. "Obstacle Avoidance and Environmental Adaptability Analysis of Snake-like Robot Based on Deep Learning." Journal of Physics: Conference Series 2146, no. 1 (January 1, 2022): 012037. http://dx.doi.org/10.1088/1742-6596/2146/1/012037.

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Abstract Aiming at the problems of high complexity and low accuracy of visual depth map feature recognition, a graph recognition algorithm based on principal component direction depth gradient histogram (pca-hodg) is designed in this study. In order to obtain high-quality depth map, it is necessary to calculate the parallax of the visual image. At the same time, in order to obtain the quantized regional shape histogram, it is necessary to carry out edge detection and gradient calculation on the depth map, then reduce the dimension of the depth map combined with the principal component, and use the sliding window detection method to reduce the dimension again to realize the feature extraction of the depth map. The results show that compared with other algorithms, the pca-hodg algorithm designed in this study improves the average classification accuracy and significantly reduces the average running time. This shows that the algorithm can reduce the running time by reducing the dimension, extract the depth map features more accurately, and has good robustness.

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KUO, CHUNG-HSIEN, HUNG-CHYUN CHOU, SHOU-WEI CHI, and YU-DE LIEN. "VISION-BASED OBSTACLE AVOIDANCE NAVIGATION WITH AUTONOMOUS HUMANOID ROBOTS FOR STRUCTURED COMPETITION PROBLEMS." International Journal of Humanoid Robotics 10, no. 03 (September 2013): 1350021. http://dx.doi.org/10.1142/s0219843613500217.

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Biped humanoid robots have been developed to successfully perform human-like locomotion. Based on the use of well-developed locomotion control systems, humanoid robots are further expected to achieve high-level intelligence, such as vision-based obstacle avoidance navigation. To provide standard obstacle avoidance navigation problems for autonomous humanoid robot researches, the HuroCup League of Federation of International Robot-Soccer Association (FIRA) and the RoboCup Humanoid League defined the conditions and rules in competitions to evaluate the performance. In this paper, the vision-based obstacle avoidance navigation approaches for humanoid robots were proposed in terms of combining the techniques of visual localization, obstacle map construction and artificial potential field (APF)-based reactive navigations. Moreover, a small-size humanoid robot (HuroEvolutionJR) and an adult-size humanoid robot (HuroEvolutionAD) were used to evaluate the performance of the proposed obstacle avoidance navigation approach. The navigation performance was evaluated with the distance of ground truth trajectory collected from a motion capture system. Finally, the experiment results demonstrated the effectiveness of using vision-based localization and obstacle map construction approaches. Moreover, the APF-based navigation approach was capable of achieving smaller trajectory distance when compared to conventional just-avoiding-nearest-obstacle-rule approach.

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Pan, Zhenhua, Dongfang Li, Kun Yang, and Hongbin Deng. "Multi-Robot Obstacle Avoidance Based on the Improved Artificial Potential Field and PID Adaptive Tracking Control Algorithm." Robotica 37, no. 11 (April 16, 2019): 1883–903. http://dx.doi.org/10.1017/s026357471900033x.

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SummaryAs for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

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Rosales-Villacrés, María de Lourdes, Cristián Oyanadel, Diana Changotasig-Loja, and Wenceslao Peñate-Castro. "Effects of a Mindfulness and Acceptance-Based Program on Intimate Relationships in a Youth Sample: A Randomized Controlled Trial." Behavioral Sciences 11, no. 6 (June 9, 2021): 84. http://dx.doi.org/10.3390/bs11060084.

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Intimate relationship conflicts in young people are crucial experiences for change. They can lead to more or less satisfactory relationships, depending on individuals’ skills to cope with these conflicts. This may or may not lead to violence in couples. Acceptance and self-regulation processes are an effective strategy to address individual factors such as avoidance and anxiety in intimate relationships of people in these age groups, thus preventing violence. The aim of this study was to assess the effects of an eight-session mindfulness and acceptance-based program (MAP). Participants (n = 40), who were aged from 18 to 25 years old, were randomly assigned to a group receiving the MAP or an active control group. Outcome measures were anxiety about abandonment, intimacy avoidance (Experiences in Close Relationships scale), well-being (Psychological Well-being Scale), dispositional mindfulness (Five Facet Mindfulness Questionnaire) and flexibility (Acceptance and Action Questionnaire-II). Measures were taken at pre-intervention, post-intervention and follow-up. Results showed that the MAP decreased anxiety (p = 0.025) and avoidance (p = 0.01) and increased mindfulness (p < 0.001) and flexibility (p = 0.001). In general, these improvements persisted at follow-up. Results are discussed in relation to the usefulness of mindfulness-acceptance strategies to cope with non-pathological intimate relationship conflicts.

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Habib, Maki K. "Real Time Mapping and Dynamic Navigation for Mobile Robots." International Journal of Advanced Robotic Systems 4, no. 3 (September 1, 2007): 35. http://dx.doi.org/10.5772/5681.

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This paper discusses the importance, the complexity and the challenges of mapping mobile robot's unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.

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Stamoulis, Kostantinos A., Jade M. S. Delevaux, Ivor D. Williams, Alan M. Friedlander, Jake Reichard, Keith Kamikawa, and Euan S. Harvey. "Incorporating reef fish avoidance behavior improves accuracy of species distribution models." PeerJ 8 (June 3, 2020): e9246. http://dx.doi.org/10.7717/peerj.9246.

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Species distribution models (SDMs) are used to interpret and map fish distributions based on habitat variables and other drivers. Reef fish avoidance behavior has been shown to vary in the presence of divers and is primarily driven by spearfishing pressure. Diver avoidance behavior or fish wariness may spatially influence counts and other descriptive measures of fish assemblages. Because fish assemblage metrics are response variables for SDMs, measures of fish wariness may be useful as predictors in SDMs of fishes targeted by spearfishing. We used a diver operated stereo-video system to conduct fish surveys and record minimum approach distance (MAD) of targeted reef fishes inside and outside of two marine reserves on the island of Oʻahu in the main Hawaiian Islands. By comparing MAD between sites and management types we tested the assumption that it provides a proxy for fish wariness related to spearfishing pressure. We then compared the accuracy of SDMs which included MAD as a predictor with SDMs that did not. Individual measures of MAD differed between sites though not management types. When included as a predictor, MAD averaged at the transect level greatly improved the accuracy of SDMs of targeted fish biomass.

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Ko, Jung-Hwan. "2D Spatial-Map Construction for Workers Identification and Avoidance of AGV." Journal of the Institute of Electronics Engineers of Korea 49, no. 9 (September 25, 2012): 347–52. http://dx.doi.org/10.5573/ieek.2012.49.9.347.

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Choi, Young-In, Jae-Hoon Cho, and Yong-Tae Kim. "Collision Avoidance Algorithm of Mobile Robots at Grid Map Intersection Point." INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS 20, no. 2 (June 30, 2020): 96–104. http://dx.doi.org/10.5391/ijfis.2020.20.2.96.

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Yoshioka, Hitoshi, Hirotada Hashimoto, and Hidenari Makino. "Decision-making algorithm for ship collision avoidance with collision risk map." Ocean Engineering 286 (October 2023): 115705. http://dx.doi.org/10.1016/j.oceaneng.2023.115705.

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Sajedifard, Mohammad, and Zahra Sajedifard. "High school students’ achievement goal adoption: Evidence from neglected rural high schools in Iran." International Journal of Education and Learning 4, no. 1 (April 7, 2022): 58–64. http://dx.doi.org/10.31763/ijele.v4i1.609.

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The study aimed to examine rural high schoolers’ achievement goal preferences and the potential gender variations in a neglected rural context in Iran. To this end, a sample of 252 high schoolers answered Elliott and Murayama’s (2008) Achievement Goal Questionnaire-Revised (AGQ-R). Quantitative results indicated the prevalence of mastery approach (MAp) and performance approach (PAp) goals, followed by performance avoidance (PAv) and mastery avoidance (MAv) goals. Further, an examination of gender differences indicated no significant differences between male and female high schoolers in their adoption of MAp, PAp and MAv goals. However, a significant difference was observed between male and female students in their resort to PAv goal. Results may have implications for different individuals in educational settings such as educational authorities, teachers, and counselors as well as researchers.

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Kwaśniewski, Konrad K., and Zdzisław Gosiewski. "Genetic Algorithm for Mobile Robot Route Planning with Obstacle Avoidance." Acta Mechanica et Automatica 12, no. 2 (June 1, 2018): 151–59. http://dx.doi.org/10.2478/ama-2018-0024.

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Abstract Nowadays many public and private institutions begin space studies projects. Among many problems to solve there is a planet exploration. Now rovers are controlled directly from the Earth, e.g. Opportunity. Missions must be planned on the Earth using simulators. Much better will be when the mission planner could set the target area and work to do and the rover will perform it independently. The solution is to make it autonomous. Without need of external path planning the rover can cover a much longer distance. To make autonomous rovers real it is necessary to implement a target leaded obstacle avoidance algorithm. Solutions based on graph algorithms use a lot of computing power. The others use intelligent methods such as neural networks or fuzzy logic but their efficiency in a very complex environment is quite low. This work presents an obstacle avoidance algorithm which uses the genetic path finding algorithm. The actual version is based on the 2D map which is built by the robot and the 2nd degree B-spline is used for the path model. The performance in the most cases is high using only one processor thread. The GA can be also easily multithreaded. Another feature of the algorithm is that, due to the GA random nature, the chosen path can differ each time on the same map. The paper shows the results of the simulation tests. The maps have the various complexity levels. On every map one hundred tests were carried out. The algorithm brought the robot to the target successfully in the majority of runs.

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Liang, Quan, Dong Hai Su, Jie Wang, and Ye Mu Wang. "The Closed Impeller Milling Avoidance Programming Algorithm." Advanced Materials Research 753-755 (August 2013): 1270–73. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1270.

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An automatically correction algorithm was promoted to solve the problem that most of the commercial CAD/CAM software can only detect the collision, but can not generate collision-free tool path on cutting path planning. The algorithm uses the configuration space theory to map the boundary into the 2D configuration space, and then the 3D space interference collision problem was transformed into 2D space. Finally, the algorithm was used to generate cutting path of a closed impellers runner. From the result of cutting path planning, the proposed algorithm was able to avoid the interference in the process of tool path planning about closed impeller.

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Fisher, Carla L., Gemme Campbell-Salome, Diliara Bagautdinova, Kevin B. Wright, Larry F. Forthun, Kelsey C. Bacharz, M. Devyn Mullis, et al. "Young Adult Caregiving Daughters and Diagnosed Mothers Navigating Breast Cancer Together: Open and Avoidant Communication and Psychosocial Outcomes." Cancers 15, no. 15 (July 29, 2023): 3864. http://dx.doi.org/10.3390/cancers15153864.

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For many diagnosed mothers and their daughters, breast cancer is a shared experience. However, they struggle to talk about cancer. This is particularly true when the daughter is in adolescence or young adulthood, as they tend to be more avoidant, which is associated with poorer biopsychosocial outcomes. When daughters are their mother’s caregivers, daughters’ burden and distress are heightened. Young adult caregiving daughters (YACDs) are the second most common family caregiver and encounter more distress and burden than other caregiver types. Yet, YACDs and their diagnosed mothers receive no guidance on how to talk about cancer. Thirty-nine mother/YACD pairs participated in an online survey to identify challenging topics and strategies for talking about cancer, and to explore associations between openness/avoidance and psychosocial outcomes. YACDs and mothers reported the same challenging topics (death, treatment-related issues, negative emotions, relational challenges, YACDs’ disease risk) but differed on why they avoided the topic. YACDs and mothers identified the same helpful approaches to navigate conversations (openness, staying positive, third-party involvement, avoidance). Avoidance was correlated with more distress whereas openness was correlated with better psychosocial outcomes. These results provide a psychosocial map for a mother-YACD communication skills intervention, which is key to promoting healthy outcomes.

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Hu, Xiaodong, Xuexiang Huang, Tianjian Hu, Zhong Shi, and Hongkun Li. "Coupling minimization with obstacles avoidance of free-floating space robots based on hybrid map in configuration space." International Journal of Advanced Robotic Systems 15, no. 6 (November 1, 2018): 172988141881655. http://dx.doi.org/10.1177/1729881418816557.

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To avoid the saturation of momentum wheels and the harm due to the thruster plume during the on-orbital manipulation, space robots usually stay in a free-floating state which follows the linear and angular momentum conservation leading to a kinematic coupling effect of the satellite base and the space manipulator. Emphasizing the stability of satellite base and execution safety, it is significant to minimize the kinematic coupling effect as well as avoid obstacles in the environment. Nevertheless, coupling minimization and obstacles avoidance are considered separately in previous work. By applying a hybrid map in the Configuration space, this article proposes a unified method dealing with the above two problems together. First, coupling factors are defined to evaluate the kinematic coupled effect which can be described by a coupling map; second, an obstruction map is generated by transforming obstacles in the Cartesian space to the Configuration space; the proposed hybrid map is finally generated from an overlay of a coupling map and an obstruction map. Numerical simulations verify the effectiveness of the method on a two degree-of-freedom planar space robot.

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Chen, Chin S., Chia J. Lin, Chun C. Lai, and Si Y. Lin. "Velocity Estimation and Cost Map Generation for Dynamic Obstacle Avoidance of ROS Based AMR." Machines 10, no. 7 (June 22, 2022): 501. http://dx.doi.org/10.3390/machines10070501.

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In the past few years, due to the growth of the open-source community and the popularity of perceptual computing resources, the ROS (Robotic Operating System)Ecosystem has been widely shared and used in academia, industrial applications, and service fields. With the advantages of reusability of algorithms and system modularity, service robot applications are flourishing via the released ROS navigation framework. In the ROS navigation framework, the grid cost maps are majorly designed for path planning and obstacle avoidance with range sensors. However, the robot will often collide with dynamic obstacles since the velocity information is not considered within the navigation framework in time. This study aims to improve the feasibility of high-speed dynamic obstacle avoidance for an ROS-based mobile robot. In order to enable the robot to detect and estimate dynamic obstacles from a first-person perspective, vision tracking and a laser ranger with an Extend Kalman Filter (EKF) have been applied. In addition, an innovative velocity obstacle layer with truncated distance is implemented for the path planner to analyze the performances between the simulated and actual avoidance behavior. Finally, via the velocity obstacle layer, as the robot faces the high-speed obstacle, safe navigation can be achieved.

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Yamashita, Atsushi, Masaaki Kitaoka, and Toru Kaneko. "Motion Planning of Biped Robot Equipped with Stereo Camera Using Grid Map." International Journal of Automation Technology 5, no. 5 (September 5, 2011): 639–47. http://dx.doi.org/10.20965/ijat.2011.p0639.

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Recognizing its surroundings is important for biped robots seeking a destination. In this paper, we propose a motion planning method of a biped robot including path planning and obstacle avoidance. The robot obtains distance information on its surrounding environment from images captured by a stereo camera system, and generates a 3D map, then, builds a 2D grid map that locates flat floor regions, obstacle regions, bump regions, gate regions, and un-measured regions to decide its path by using the 2D grid map. Experimental results confirm the effectiveness of the proposed method.

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Cao, Meng Long, and Li Na Sun. "Study on Intelligent Obstacle Avoidance and Autonomous Navigation." Applied Mechanics and Materials 182-183 (June 2012): 1333–37. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1333.

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Precise navigation and localization of the autonomous rover in unknown environment is important both for its own safety as well as for its ability to accomplish engineering and scientific objectives. In order to navigation autonomously the rover should have the ability of apperceiving the environment and avoiding the obstacles. Laser range finder is used to rebuild the environment and fuzzy reasoning method is used to avoid obstacles. Most importantly the rover process the sensor data to produce an estimate of its position while concurrently building a map of the environment. The improved filter algorithm is proposed to make the method feasible.

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Frankenberry, Nancy. "Map is Not Territory, Menu is Not Meal." Method & Theory in the Study of Religion 31, no. 1 (February 12, 2019): 3–13. http://dx.doi.org/10.1163/15700682-12341458.

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Abstract This article focuses on Jonathan Z. Smith’s 1978 essay, “Map is Not Territory,” in terms of its definition of religion, allegiance to anthropology and history, and avoidance of relativism. Updated to the author’s situation forty years later, it articulates the relation between map and territory as one of asymmetrical dependence governed by the rule that the concrete includes the abstract and exceeds it in value. Reading Smith’s essay in light of Donald Davidson’s “On the Very Idea of a Conceptual Scheme” provides a philosophical argument against radical relativism. Two brief aperçu about Smith frame this account.

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MINAMOTO, Kenji, Nobuhiro OKADA, and Eiji KONDO. "Collision Avoidance of a Visuo-Motor System with a Self Organizing Map." Proceedings of Conference of Kyushu Branch 2002.55 (2002): 341–42. http://dx.doi.org/10.1299/jsmekyushu.2002.55.341.

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Zhou, Qiang, Danping Zou, and Peilin Liu. "Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs." Industrial Robot: An International Journal 45, no. 2 (March 19, 2018): 227–36. http://dx.doi.org/10.1108/ir-07-2017-0126.

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Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs. Findings The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects. Research limitations/implications The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV. Practical implications The developed approach could be valuable to applications in indoors. Originality/value This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

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Kim, SungHee, Yasushi Hada, and Koji Kanayama. "Electric Field Strength Simulation Using 2D-Environment Map Generated by Tele-Operated Mobile Robot." Journal of Robotics and Mechatronics 34, no. 3 (June 20, 2022): 569–75. http://dx.doi.org/10.20965/jrm.2022.p0569.

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In this study, we demonstrate the avoidance of the “lost robot” situation when wireless communication is interrupted. In our proposed method, the mobile robot measures the unknown environmental shape using a laser range finder. The sensor data and additional information (thickness and material characteristics) of the real environment are combined into the line segment map. We found that the electric field strength can be simulated using the line segment map. Experimental results verify the effectiveness of our proposed method.

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Jia, Guanwei, Xiaoying Li, Dongming Zhang, Weiqing Xu, Haojie Lv, Yan Shi, and Maolin Cai. "Visual-SLAM Classical Framework and Key Techniques: A Review." Sensors 22, no. 12 (June 17, 2022): 4582. http://dx.doi.org/10.3390/s22124582.

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With the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoidance. This review starts with the development of SLAM (Simultaneous Localization and Mapping) and proceeds to a review of V-SLAM (Visual-SLAM) from its proposal to the present, with a summary of its historical milestones. In this context, the five parts of the classic V-SLAM framework—visual sensor, visual odometer, backend optimization, loop detection, and mapping—are explained separately. Meanwhile, the details of the latest methods are shown; VI-SLAM (Visual inertial SLAM) is reviewed and extended. The four critical techniques of V-SLAM and its technical difficulties are summarized as feature detection and matching, selection of keyframes, uncertainty technology, and expression of maps. Finally, the development direction and needs of the V-SLAM field are proposed.

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LINDEMANN, STEPHANIE. "Listening with an attitude: A model of native-speaker comprehension of non-native speakers in the United States." Language in Society 31, no. 3 (July 2002): 419–41. http://dx.doi.org/10.1017/s0047404502020286.

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This study investigates whether there is a relationship between negative attitudes toward non-native speakers and poor comprehension of those speakers. Twelve native English speakers whose attitudes toward Koreans had been assessed were asked to complete an interactional map task paired with native Korean speakers. In the task, some but not all of those who had been assessed as having negative attitudes toward Koreans were found to use either strategies that were described as problematizing their partners' utterances, or strategies that were described as avoidance. All participants completed the map task reasonably successfully except where the native English speaker used avoidance strategies, suggesting that the relationship between attitude and comprehension is mediated by the native speaker's choice of strategies. However, there appeared to be a direct relationship between attitude and perceived success of interactions, which may ultimately have the same consequences for interactants as if the relationship were between attitude and actual success.

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Pathak, Rachit Mehul, and Ajay Varma Mudunuri. "Autonomous Obstacle Detection and Avoidance in Drones." Innovative Research Thoughts 9, no. 4 (2023): 73–85. http://dx.doi.org/10.36676/irt.2023-v9i4-011.

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Drone technology has recently advanced, and object detection technology is already evolving. These technologies can be used to find illegal immigrants, locate missing people and items, and detect industrial and natural disasters. In this research, we investigate how to improve object detection performance in such cases. Photography was carried out in a setting where it was difficult to identify objects. The experimental data was based on images taken under various situations, such as changing the drone's altitude, shooting pictures in the dark, and so on. In this work, we recommend a way to make YOLO models more effective at detecting objects. To determine the key indicators, we will input the collected data into the CNN model and the YOLO model, respectively. Precision, recall, F-1 score, and mAP are the major metrics of evaluation. On the basis of the data comparing the CNN model with the YOLO model, an inference will then be drawn.

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Yan, Mingzhong, Daqi Zhu, and Simon X. Yang. "Complete Coverage Path Planning in an Unknown Underwater Environment Based on D-S Data Fusion Real-Time Map Building." International Journal of Distributed Sensor Networks 8, no. 10 (October 1, 2012): 567959. http://dx.doi.org/10.1155/2012/567959.

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A real-time map-building system is proposed for an autonomous underwater vehicle (AUV) to build a map of an unknown underwater environment. The system, using the AUV's onboard sensor information, includes a neurodynamics model proposed for complete coverage path planning and an evidence theoretic method proposed for map building. The complete coverage of the environment guarantees that the AUV can acquire adequate environment information. The evidence theory is used to handle the noise and uncertainty of the sensor data. The AUV dynamically plans its path with obstacle avoidance through the landscape of neural activity. Concurrently, real-time sensor data are “fused” into a two-dimensional (2D) occupancy grid map of the environment using evidence inference rule based on the Dempster-Shafer theory. Simulation results show a good quality of map-building capabilities and path-planning behaviors of the AUV.

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Belghith, Abdelfettah, Mohamed Belhassen, Amine Dhraief, Nour Elhouda Dougui, and Hassan Mathkour. "Autonomic Obstacle Detection and Avoidance in MANETs Driven by Cartography Enhanced OLSR." Mobile Information Systems 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/820401.

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The presence of obstructing obstacles severely degrades the efficiency of routing protocols in MANETs. To mitigate the effect of these obstructing obstacles, routing in MANETs is usually based on thea prioriknowledge of the obstacle map. In this paper, we investigate rather the dynamic and autonomic detection of obstacles that might stand within the network. This is accomplished using the enhanced cartography optimized link state routing CE-OLSR with no extra signaling overhead. The evaluation of the performance of our proposed detection scheme is accomplished through extensive simulations using OMNET++. Results clearly show the ability of our proposed scheme to accurately delimit the obstacle area with high coverage and efficient precision ratios. Furthermore, we integrated the proposed scheme into CE-OLSR to make it capable of autonomously detecting and avoiding obstacles. Simulation results show the effectiveness of such an integrated protocol that provides the same route validity as that of CE-OLSR-OA which is based on thea prioriknowledge of the obstructing obstacle map.

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Kownacki, Cezary. "A concept of laser scanner designed to realize 3D obstacle avoidance for a fixed-wing UAV." Robotica 34, no. 2 (June 9, 2014): 243–57. http://dx.doi.org/10.1017/s0263574714001404.

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SUMMARYThis paper presents a concept of a laser scanner framework designed for obstacle avoidance used on mini fixed-wing unmanned aerial vehicles (UAVs) flying in outdoor environments. The innovation is a conical field of view that guarantees tri-dimensional (3D) obstacle detection and localization at any pitch or roll angle. This advantage is very important for the case of fixed-wing UAV flights where the attitude is changing rapidly. Measurement sequences create a map that is represented by a circular grid with the center fitted to thex-axis of the UAV's body, lying in the plane normal to the velocity vector and projected in the front of UAV. This means that the map cells contain differences between the safety zone radius and distances acquired from area in close proximity to the flight path. Actual UAV attitude can be compensated by rotation and shift of two masks of gains that are applied to the map to determine pitch and roll commands. Results of the simulation research conducted on the designed concept are very promising, as they present a combination of lateral and vertical obstacle avoidance. Based on the experience with laser rangefinders operating on a real UAV, it can be convincingly determined that the concept of the laser scanner is able to be brought into reality.

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Wu, Peng, Shaorong Xie, Hengli Liu, Ming Li, Hengyu Li, Yan Peng, Xiaomao Li, and Jun Luo. "Autonomous obstacle avoidance of an unmanned surface vehicle based on cooperative manoeuvring." Industrial Robot: An International Journal 44, no. 1 (January 16, 2017): 64–74. http://dx.doi.org/10.1108/ir-04-2016-0127.

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Purpose Autonomous obstacle avoidance is important in unmanned surface vehicle (USV) navigation. Although the result of obstacle detection is often inaccurate because of the inherent errors of LIDAR, conventional methods typically emphasize on a single obstacle-avoidance algorithm and neglect the limitation of sensors and safety in a local region. Conventional methods also fail in seamlessly integrating local and global obstacle avoidance algorithms. This paper aims to present a cooperative manoeuvring approach including both local and global obstacle avoidance. Design/methodology/approach The global algorithm used in our USV is the Artificial Potential Field-Ant Colony Optimization (APF-ACO) obstacle-avoidance algorithm, which plans a relative optimal path on the specified electronic map before the cruise of USV. The local algorithm is a multi-layer obstacle-avoidance framework based on a single LIDAR to present an efficient solution to USV path planning in the case of sensor errors and collision risks. When obstacles are within a layer, the USV uses a corresponding obstacle-avoidance algorithm. Then the USV moves towards the global direction according to fuzzy rules in the fuzzy layer. Findings The presented method offers a solution for obstacle avoidance in a complex environment. The USV follows the global trajectory planed by the APF-ACO algorithm. While, the USV can bypass current obstacle in the local region based on the multi-layer method effectively. This fact was validated by simulations and field trials. Originality/value The method presented in this paper takes advantage of algorithm integration that remedies errors of obstacle detection. Simulation and experiments were also conducted for performance evaluation.

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Raja, Rekha, S. N. Shome, S. Nandy, and R. Ray. "Obstacle Avoidance and Navigation of Autonomous Mobile Robot." Advanced Materials Research 403-408 (November 2011): 4633–42. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4633.

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This paper presents a hybrid obstacle avoidance methodology for autonomous navigation of a mobile robot in an unstructured environment. Decision is taken based on the classical method depending on the environmental scenario where the space between multiple obstacles is measured and the feasibility of passing the robot through any immediate pair of obstacles examined. In other cases, the decision is taken by the Fuzzy Logic controller. The developed algorithm is simulated and experimentally validated with a mobile robot platform equipped with forward-looking sonar for obstacle detection. Odometry sensors assist in localization of the mobile robot. The developed algorithm is found adequately intelligent to navigate the robot from any start position through to the desired goal position avoiding obstacles, and without taking recourse to any pre-built map. The simulated results exhibit fair agreement with the experimental results.

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Park, Seung Hwan, and Beom Hee Lee. "Analysis of robot collision characteristics using the concept of the collision map." Robotica 24, no. 3 (November 17, 2005): 295–303. http://dx.doi.org/10.1017/s0263574705002122.

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Robot collision characteristics are analyzed by using the idea of the collision map. This analysis consists of the translations of the collision region on the collision map and they correspond to parallel movements of the original robot path. These translations are investigated in several cases and applied to general situations in which two robots are moving or working in a common workspace. Also, the collision characteristics are analyzed for a few special situations where the analysis of collision characteristics is crucial and the resultant solution for collision avoidance can be obtained.

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Chen, Guangda, Shunyi Yao, Jun Ma, Lifan Pan, Yu’an Chen, Pei Xu, Jianmin Ji, and Xiaoping Chen. "Distributed Non-Communicating Multi-Robot Collision Avoidance via Map-Based Deep Reinforcement Learning." Sensors 20, no. 17 (August 27, 2020): 4836. http://dx.doi.org/10.3390/s20174836.

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It is challenging to avoid obstacles safely and efficiently for multiple robots of different shapes in distributed and communication-free scenarios, where robots do not communicate with each other and only sense other robots’ positions and obstacles around them. Most existing multi-robot collision avoidance systems either require communication between robots or require expensive movement data of other robots, like velocities, accelerations and paths. In this paper, we propose a map-based deep reinforcement learning approach for multi-robot collision avoidance in a distributed and communication-free environment. We use the egocentric local grid map of a robot to represent the environmental information around it including its shape and observable appearances of other robots and obstacles, which can be easily generated by using multiple sensors or sensor fusion. Then we apply the distributed proximal policy optimization (DPPO) algorithm to train a convolutional neural network that directly maps three frames of egocentric local grid maps and the robot’s relative local goal positions into low-level robot control commands. Compared to other methods, the map-based approach is more robust to noisy sensor data, does not require robots’ movement data and considers sizes and shapes of related robots, which make it to be more efficient and easier to be deployed to real robots. We first train the neural network in a specified simulator of multiple mobile robots using DPPO, where a multi-stage curriculum learning strategy for multiple scenarios is used to improve the performance. Then we deploy the trained model to real robots to perform collision avoidance in their navigation without tedious parameter tuning. We evaluate the approach with multiple scenarios both in the simulator and on four differential-drive mobile robots in the real world. Both qualitative and quantitative experiments show that our approach is efficient and outperforms existing DRL-based approaches in many indicators. We also conduct ablation studies showing the positive effects of using egocentric grid maps and multi-stage curriculum learning.

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Matsumura, Koki. "Simulation of Obstacles Avoidance by Chaotic Mobile Robot Using the Deformed Bernoulli's Map." IEEJ Transactions on Electronics, Information and Systems 119, no. 5 (1999): 603–14. http://dx.doi.org/10.1541/ieejeiss1987.119.5_603.

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Jung, Euigon, Wonho Song, and Hyun Myung. "High-Definition Map-based Local Path Planning for Dynamic and Static Obstacle Avoidance." Journal of Korea Robotics Society 16, no. 2 (June 1, 2021): 112–21. http://dx.doi.org/10.7746/jkros.2021.16.2.112.

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Yelbaşı, Özen, and Emin Germen. "A SELF ORGANIZING MAP BASED APPROACH FOR CONGESTION AVOIDANCE IN AUTONOMOUS IP NETWORKS." Neural Network World 25, no. 2 (2015): 139–60. http://dx.doi.org/10.14311/nnw.2015.25.007.

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Nagavarapu, Sarat Chandra, Leena Vachhani, and Arpita Sinha. "Multi-Robot Graph Exploration and Map Building with Collision Avoidance: A Decentralized Approach." Journal of Intelligent & Robotic Systems 83, no. 3-4 (December 8, 2015): 503–23. http://dx.doi.org/10.1007/s10846-015-0309-9.

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Lee, Kibeom, and Dongsuk Kum. "Collision Avoidance/Mitigation System: Motion Planning of Autonomous Vehicle via Predictive Occupancy Map." IEEE Access 7 (2019): 52846–57. http://dx.doi.org/10.1109/access.2019.2912067.

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Journal articles on the topic 'Avoidance Map'

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