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Journal articles on the topic 'Robotics, software architecture, SLAM'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Mamri, Ayoub, Mohamed Abouzahir, Mustapha Ramzi, and Rachid Latif. "ORB-SLAM accelerated on heterogeneous parallel architectures." E3S Web of Conferences 229 (2021): 01055. http://dx.doi.org/10.1051/e3sconf/202122901055.

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SLAM algorithm permits the robot to cartography the desired environment while positioning it in space. It is a more efficient system and more accredited by autonomous vehicle navigation and robotic application in the ongoing research. Except it did not adopt any complete end-to-end hardware implementation yet. Our work aims to a hardware/software optimization of an expensive computational time functional block of monocular ORB-SLAM2. Through this, we attempt to implement the proposed optimization in FPGA-based heterogeneous embedded architecture that shows attractive results. Toward this, we adopt a comparative study with other heterogeneous architecture including powerful embedded GPGPU (NVIDIA Tegra TX1) and high-end GPU (NVIDIA GeForce 920MX). The implementation is achieved using high-level synthesis-based OpenCL for FPGA and CUDA for NVIDIA targeted boards.

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2

Mihálik, Michal, Branislav Malobický, Peter Peniak, and Peter Vestenický. "The New Method of Active SLAM for Mapping Using LiDAR." Electronics 11, no. 7 (March 30, 2022): 1082. http://dx.doi.org/10.3390/electronics11071082.

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In this article, we propose a new approach to addressing the issue of active SLAM. In this design, we used the already functional SLAM algorithm, which we modified for our case. Matlab was used as the main software tool. All proposed methods were experimentally verified on a mobile robotic system. We used LiDAR as the primary sensor. After mapping the environment, we created a grid map. The grid map may be used for the navigation of the mobile robotic system, but the navigation and control of the mobile robotic system are not involved in this article. The result of the whole process is an autonomous mapping of the environment.

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3

Song, Jooeun, and Joongjin Kook. "Mapping Server Collaboration Architecture Design with OpenVSLAM for Mobile Devices." Applied Sciences 12, no. 7 (April 5, 2022): 3653. http://dx.doi.org/10.3390/app12073653.

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SLAM technology, which is used for spatial recognition in autonomous driving and robotics, has recently emerged as an important technology to provide high-quality AR contents on mobile devices due to the spread of XR and metaverse technologies. In this paper, we designed, implemented, and verified the SLAM system that can be used on mobile devices. Mobile SLAM is composed of a stand-alone type that directly performs SLAM operation on a mobile device and a mapping server type that additionally configures a mapping server based on FastAPI to perform SLAM operation on the server and transmits data for map visualization to a mobile device. The mobile SLAM system proposed in this paper mixes the two types in order to make SLAM operation and map generation more efficient. The stand-alone type of SLAM system was configured as an Android app by porting the OpenVSLAM library to the Unity engine, and the map generation and performance were evaluated on desktop PCs and mobile devices. The mobile SLAM system in this paper is an open-source project, so it is expected to help develop AR contents based on SLAM in a mobile environment.

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Hastürk, Özgür, and Aydan M. Erkmen. "DUDMap: 3D RGB-D mapping for dense, unstructured, and dynamic environment." International Journal of Advanced Robotic Systems 18, no. 3 (May 1, 2021): 172988142110161. http://dx.doi.org/10.1177/17298814211016178.

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Simultaneous localization and mapping (SLAM) problem has been extensively studied by researchers in the field of robotics, however, conventional approaches in mapping assume a static environment. The static assumption is valid only in a small region, and it limits the application of visual SLAM in dynamic environments. The recently proposed state-of-the-art SLAM solutions for dynamic environments use different semantic segmentation methods such as mask R-CNN and SegNet; however, these frameworks are based on a sparse mapping framework (ORBSLAM). In addition, segmentation process increases the computational power, which makes these SLAM algorithms unsuitable for real-time mapping. Therefore, there is no effective dense RGB-D SLAM method for real-world unstructured and dynamic environments. In this study, we propose a novel real-time dense SLAM method for dynamic environments, where 3D reconstruction error is manipulated for identification of static and dynamic classes having generalized Gaussian distribution. Our proposed approach requires neither explicit object tracking nor object classifier, which makes it robust to any type of moving object and suitable for real-time mapping. Our method eliminates the repeated views and uses consistent data that enhance the performance of volumetric fusion. For completeness, we compare our proposed method using different types of high dynamic dataset, which are publicly available, to demonstrate the versatility and robustness of our approach. Experiments show that its tracking performance is better than other dense and dynamic SLAM approaches.

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5

Goertzel, Ben, David Hanson, and Gino Yu. "A Software Architecture for Generally Intelligent Humanoid Robotics." Procedia Computer Science 41 (2014): 158–63. http://dx.doi.org/10.1016/j.procs.2014.11.099.

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6

Cañas Plaza, José María, Jesús Ruiz Ayúcar, Carlos Agüero Durán, and Francisco Martín Rico. "Jde-neoc: component oriented software architecture for robotics." Journal of Physical Agents (JoPha) 1, no. 1 (2007): 1–6. http://dx.doi.org/10.14198/jopha.2007.1.1.01.

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7

Medvidovic, Nenad, Hossein Tajalli, Joshua Garcia, Ivo Krka, Yuriy Brun, and George Edwards. "Engineering Heterogeneous Robotics Systems: A Software Architecture-Based Approach." Computer 44, no. 5 (May 2011): 62–71. http://dx.doi.org/10.1109/mc.2010.368.

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8

Khosoussi, Kasra, Matthew Giamou, Gaurav S. Sukhatme, Shoudong Huang, Gamini Dissanayake, and Jonathan P. How. "Reliable Graphs for SLAM." International Journal of Robotics Research 38, no. 2-3 (January 22, 2019): 260–98. http://dx.doi.org/10.1177/0278364918823086.

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Estimation-over-graphs (EoG) is a class of estimation problems that admit a natural graphical representation. Several key problems in robotics and sensor networks, including sensor network localization, synchronization over a group, and simultaneous localization and mapping (SLAM) fall into this category. We pursue two main goals in this work. First, we aim to characterize the impact of the graphical structure of SLAM and related problems on estimation reliability. We draw connections between several notions of graph connectivity and various properties of the underlying estimation problem. In particular, we establish results on the impact of the weighted number of spanning trees on the D-optimality criterion in 2D SLAM. These results enable agents to evaluate estimation reliability based only on the graphical representation of the EoG problem. We then use our findings and study the problem of designing sparse SLAM problems that lead to reliable maximum likelihood estimates through the synthesis of sparse graphs with the maximum weighted tree connectivity. Characterizing graphs with the maximum number of spanning trees is an open problem in general. To tackle this problem, we establish several new theoretical results, including the monotone log-submodularity of the weighted number of spanning trees. We exploit these structures and design a complementary greedy–convex pair of efficient approximation algorithms with provable guarantees. The proposed synthesis framework is applied to various forms of the measurement selection problem in resource-constrained SLAM. Our algorithms and theoretical findings are validated using random graphs, existing and new synthetic SLAM benchmarks, and publicly available real pose-graph SLAM datasets.

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9

Alsadik, Bashar, and Samer Karam. "The Simultaneous Localization and Mapping (SLAM)-An Overview." Journal of Applied Science and Technology Trends 2, no. 04 (November 18, 2021): 120–31. http://dx.doi.org/10.38094/jastt204117.

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Positioning is a need for many applications related to mapping and navigation either in civilian or military domains. The significant developments in satellite-based techniques, sensors, telecommunications, computer hardware and software, image processing, etc. positively influenced to solve the positioning problem efficiently and instantaneously. Accordingly, the mentioned development empowered the applications and advancement of autonomous navigation. One of the most interesting developed positioning techniques is what is called in robotics as the Simultaneous Localization and Mapping SLAM. The SLAM problem solution has witnessed a quick improvement in the last decades either using active sensors like the RAdio Detection And Ranging (Radar) and Light Detection and Ranging (LiDAR) or passive sensors like cameras. Definitely, positioning and mapping is one of the main tasks for Geomatics engineers, and therefore it's of high importance for them to understand the SLAM topic which is not easy because of the huge documentation and algorithms available and the various SLAM solutions in terms of the mathematical models, complexity, the sensors used, and the type of applications. In this paper, a clear and simplified explanation is introduced about SLAM from a Geomatical viewpoint avoiding going into the complicated algorithmic details behind the presented techniques. In this way, a general overview of SLAM is presented showing the relationship between its different components and stages like the core part of the front-end and back-end and their relation to the SLAM paradigm. Furthermore, we explain the major mathematical techniques of filtering and pose graph optimization either using visual or LiDAR SLAM and introduce a summary of the deep learning efficient contribution to the SLAM problem. Finally, we address examples of some existing practical applications of SLAM in our reality.

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Alsadik, Bashar, and Samer Karam. "The Simultaneous Localization and Mapping (SLAM)-An Overview." Surveying and Geospatial Engineering Journal 2, no. 01 (May 18, 2021): 01–12. http://dx.doi.org/10.38094/sgej1027.

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Positioning is a need for many applications related to mapping and navigation either in civilian or military domains. The significant developments in satellite-based techniques, sensors, telecommunications, computer hardware and software, image processing, etc. positively influenced to solve the positioning problem efficiently and instantaneously. Accordingly, the mentioned development empowered the applications and advancement of autonomous navigation. One of the most interesting developed positioning techniques is what is called in robotics as the Simultaneous Localization and Mapping SLAM. The SLAM problem solution has witnessed a quick improvement in the last decades either using active sensors like the RAdio Detection And Ranging (Radar) and Light Detection and Ranging (LiDAR) or passive sensors like cameras. Definitely, positioning and mapping is one of the main tasks for Geomatics engineers, and therefore it's of high importance for them to understand the SLAM topic which is not easy because of the huge documentation and algorithms available and the various SLAM solutions in terms of the mathematical models, complexity, the sensors used, and the type of applications. In this paper, a clear and simplified explanation is introduced about SLAM from a Geomatical viewpoint avoiding going into the complicated algorithmic details behind the presented techniques. In this way, a general overview of SLAM is presented showing the relationship between its different components and stages like the core part of the front-end and back-end and their relation to the SLAM paradigm. Furthermore, we explain the major mathematical techniques of filtering and pose graph optimization either using visual or LiDAR SLAM and introduce a summary of the deep learning efficient contribution to the SLAM problem. Finally, we address examples of some existing practical applications of SLAM in our reality.

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11

Malavolta, Ivano, Grace A. Lewis, Bradley Schmerl, Patricia Lago, and David Garlan. "Mining guidelines for architecting robotics software." Journal of Systems and Software 178 (August 2021): 110969. http://dx.doi.org/10.1016/j.jss.2021.110969.

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12

Erdemir, Gokhan, Ahmet Emin Kuzucuoglu, Erkan Kaplanoglu, and Yasser El-Kahlout. "Design and Implementation of Web Based Mobile Robot Control Platform for Robotics Education." Applied Mechanics and Materials 704 (December 2014): 283–87. http://dx.doi.org/10.4028/www.scientific.net/amm.704.283.

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In this paper, we present a particular case of a dynamic, real-time and efficient web-based mobile robot experiment platform (WEB.MREP) design for mobile robotic applications. The design and construction of a multipurpose and WEB.MREP for the application of different path planning and tracking, simultaneous localization and mapping (SLAM) and robot vision techniques for mobile robotic system is the main purpose of this study. The designed and constructed experiment platform consists of five main components: Festo Robotino mobile robot sets, a designed experimental area, a server software, web interfaces (user interfaces) and security measures. The designed platform provides monitoring, real-time controlling and programming of mobile robots for experimental studies and, it helps the users to achieve these studies through a standard web browser without any additional supportive software.

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13

Fang, Baofu, and Zhiqiang Zhan. "A visual SLAM method based on point-line fusion in weak-matching scene." International Journal of Advanced Robotic Systems 17, no. 2 (March 1, 2020): 172988142090419. http://dx.doi.org/10.1177/1729881420904193.

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Visual simultaneous localization and mapping (SLAM) is well-known to be one of the research areas in robotics. There are many challenges in traditional point feature-based approaches, such as insufficient point features, motion jitter, and low localization accuracy in low-texture scenes, which reduce the performance of the algorithms. In this article, we propose an RGB-D SLAM system to handle these situations, which is named Point-Line Fusion (PLF)-SLAM. We utilize both points and line segments throughout the process of our work. Specifically, we present a new line segment extraction method to solve the overlap or branch problem of the line segments, and then a more rigorous screening mechanism is proposed in the line matching section. Instead of minimizing the reprojection error of points, we introduce the reprojection error based on points and lines to get a more accurate tracking pose. In addition, we come up with a solution to handle the jitter frame, which greatly improves tracking success rate and availability of the system. We thoroughly evaluate our system on the Technische Universität München (TUM) RGB-D benchmark and compare it with ORB-SLAM2, presumably the current state-of-the-art solution. The experiments show that our system has better accuracy and robustness compared to the ORB-SLAM2.

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14

Blank, Douglas, Lisa Meeden, and Deepak Kumar. "Python robotics." ACM SIGCSE Bulletin 35, no. 1 (January 11, 2003): 317–21. http://dx.doi.org/10.1145/792548.611996.

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15

Kameyama, Michitaka. "Special Issue on Computer Architecture for Robotics." Journal of Robotics and Mechatronics 2, no. 6 (December 20, 1990): 417. http://dx.doi.org/10.20965/jrm.1990.p0417.

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In the realization of intelligent robots, highly intelligent manipulation and movement techniques are required such as intelligent man-machine interfaces, intelligent information processing for path planning and problem solutions, practical robot vision, and high-speed sensor signal processing. Thus, very high-speed processing to cope with vast amounts of data as well as the development of various algorithms has become important subjects. To fulfill such requirements, the development of high-performance computer architecture using advanced microelectronics technology is required. For these purposes, the development of implementing computer systems’ for robots will be classified as follows: (a) Use of general-purpose computers As the performance of workstations and personal computers is increased year by year, software development is the major task without requiring hardware development except the interfaces with peripheral equipment. Since current high-level languages and software can be applied, the approach is excellent in case of system development, but the processing performance is limited. (b) Use of commercially available (V) LSI chips This is an approach to design a computer system by the combination of commercially available LSIs. Since the development of both hardware and software is involved in this system development, the development period tends to be longer than in (a). These chips include general-purpose microprocessors, memory chips, digital signal processors (DSPs) and multiply-adder LSIs. Though the kinds of available chips are limited to some degree, the approach can cope with a considerably high-performance specifications because a number of chips can be flexibly used. (c) Design, development and system configuration of VLSI chips This is an approach to develop new special-purpose VLSI chips using ASIC (Application Specific Integrated Circuit) technology, that is, semicustom or full-custom technology. If these attain practical use and are marketed, they will be widely used as high-performance VLSI chips of the level (b). Since a very high-performance specification must be satisfied, the study of very high performance VLSI computer architecture becomes very important. But this approach involving chip development requires a very long period in the design-development from the determination of processor specifications to the system configuration using the fabricated chips. For the above three approaches, the order from the viewpoint of ease of development will be (a), (b) and (c), while that from the viewpoint of performance will be (c), (b) and (a). Each approach is not exclusive but is complementary each other. For example, the development of new chips by (c) can also give new impact as the components of (a) and (b). Further, the common point of these approaches is that performance improvement by highly parallel architecture becomes important. This special edition introduces, from the above standpoint, the latest information on the present state and' future prospects of the computer techniques in Japan. We hope that this edition will contribute to the development of this field.

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16

Gallagher, John C., and Steven Perretta. "WWW autonomous robotics." ACM SIGCSE Bulletin 34, no. 1 (March 2002): 13–17. http://dx.doi.org/10.1145/563517.563346.

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17

Klassner, Frank, and Christopher Continanza. "Mindstorms without robotics." ACM SIGCSE Bulletin 39, no. 1 (March 7, 2007): 175–79. http://dx.doi.org/10.1145/1227504.1227372.

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18

Ramos, Leonardo, Gabriel Lisbôa Guimarães Divino, Guilherme Cano Lopes, Breno Bernard Nicolau De França, Leonardo Montecchi, and Esther Luna Colombini. "The RoCS Framework to Support the Development of Autonomous Robots." Journal of Software Engineering Research and Development 7 (December 21, 2019): 10. http://dx.doi.org/10.5753/jserd.2019.470.

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With the expansion of autonomous robotics and its applications (e.g. medical, competition, military), the biggest hurdle in developing mobile robots lies in endowing them with the ability to interact with the environment and to make correct decisions so that their tasks can be executed successfully. However, as the complexity of robotic systems grows, the need to organize and modularize software for their correct functioning also becomes a challenge, making the development of software for controlling robots a complex and intricate task. In the robotics domain, there is a lack of reference software architectures and, although most robot architectures available in the literature facilitate the creation process with their modularity, existing solutions do not provide development guidance on reusing existing modules. Based on the well- known IBM Autonomic Computing reference architecture (known as MAPE-K), this work defines a refined architecture following the Robotics perspective. To explore the capabilities of the proposed refinement, we implemented the RoCS (Robotics and Cognitive Systems) framework for autonomous robots. We successfully tested the framework under simulated robotics scenarios that mimic typical robotics tasks and evidence the framework reuse capability. Finally, we understand the proposed framework needs further experimental evaluation, particularly, assessments on real-world scenarios.

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Krasnosky, Kristopher, Christopher Roman, and David Casagrande. "A bathymetric mapping and SLAM dataset with high-precision ground truth for marine robotics." International Journal of Robotics Research 41, no. 1 (October 11, 2021): 12–19. http://dx.doi.org/10.1177/02783649211044749.

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In recent years, sonar systems for surface and underwater vehicles have increased in resolution and become significantly less expensive. As such, these systems are viable at a wide range of price points and are appropriate for a broad set of applications on surface and underwater vehicles. However, to take full advantage of these high-resolution sensors for seafloor mapping tasks an adequate navigation solution is also required. In GPS-denied environments this usually necessitates a simultaneous localization and mapping (SLAM) technique to maintain good accuracy with minimal error accumulation. Acoustic positioning systems such as ultra short baseline (USBL) and long baseline (LBL) are sometimes deployed to provide additional bounds on the navigation solution, but the positional uncertainty of these systems is often much greater than the resolution of modern multibeam or interferometric side scan sonars. As such, subsurface vehicles often lack the means to adequately ground-truth navigation solutions and the resulting bathymetic maps. In this article, we present a dataset with four separate surveys designed to test bathymetric SLAM algorithms using two modern sonars, typical underwater vehicle navigation sensors, and high-precision (2 cm horizontal, 10 cm vertical) real-time kinematic (RTK) GPS ground truth. In addition, these data can be used to refine and improve other aspects of multibeam sonar mapping such as ray-tracing, gridding techniques, and time-varying attitude corrections.

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Ebel, Henrik, and Peter Eberhard. "Cooperative transportation: realizing the promises of robotic networks using a tailored software/hardware architecture." at - Automatisierungstechnik 70, no. 4 (March 25, 2022): 378–88. http://dx.doi.org/10.1515/auto-2021-0105.

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Abstract With cooperative transportation, the paper looks at a demanding problem from distributed robotics. At its heart, the proposed transportation scheme uses distributed model predictive control. Yet, distributed control alone does not suffice to solve the task. Thus, also distributed organization, a custom software architecture, simulation, and custom robotic hardware are dealt with, bridging the gap between distributed control theory and practical robotics. The robots are enabled to transport arbitrarily-shaped objects, automatically adapting to changing circumstances and numbers of robots.

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21

Kirill, Kirsanov. "The Architecture of Robotics Control Software for Heterogeneous Mobile Robots Network." Procedia Engineering 69 (2014): 216–21. http://dx.doi.org/10.1016/j.proeng.2014.02.224.

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Bingham, Brian S., Jeffrey M. Walls, and Ryan M. Eustice. "Development of a Flexible Command and Control Software Architecture for Marine Robotic Applications." Marine Technology Society Journal 45, no. 3 (May 1, 2011): 25–36. http://dx.doi.org/10.4031/mtsj.45.3.4.

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AbstractThis paper reports the implementation of a supervisory control framework and modular software architecture built around the lightweight communication and marshalling (LCM) publish/subscribe message passing system. In particular, we examine two diverse marine robotics applications using this modular system: (i) the development of an unmanned port security vehicle, a robotic surface platform to support first responders reacting to transportation security incidents in harbor environments, and (ii) the adaptation of a commercial off-the-shelf autonomous underwater vehicle (the Ocean-Server Iver2) for visual feature-based navigation. In both cases, the modular vehicle software infrastructures are based around the open-source LCM software library for low-latency, real-time message passing. To elucidate the real-world application of LCM in marine robotic systems, we present the software architecture of these two successful marine robotic applications and illustrate the capabilities and flexibilities of this approach to real-time marine robotics. We present benchmarking test results comparing the throughput of LCM with the Mission-Oriented Operating Suite, another robot software system popular in marine robotics. Experimental results demonstrate the capacity of the LCM framework to make large amounts of actionable information available to the operator and to allow for distributed supervisory control. We also provide a discussion of the qualitative tradeoffs involved in selecting software infrastructure for supervisory control.

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Seo, Jungwon, Jamie Paik, and Mark Yim. "Modular Reconfigurable Robotics." Annual Review of Control, Robotics, and Autonomous Systems 2, no. 1 (May 3, 2019): 63–88. http://dx.doi.org/10.1146/annurev-control-053018-023834.

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This article reviews the current state of the art in the development of modular reconfigurable robot (MRR) systems and suggests promising future research directions. A wide variety of MRR systems have been presented to date, and these robots promise to be versatile, robust, and low cost compared with other conventional robot systems. MRR systems thus have the potential to outperform traditional systems with a fixed morphology when carrying out tasks that require a high level of flexibility. We begin by introducing the taxonomy of MRRs based on their hardware architecture. We then examine recent progress in the hardware and the software technologies for MRRs, along with remaining technical issues. We conclude with a discussion of open challenges and future research directions.

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Bouhoun, Salah, Rabah Sadoun, and Mourad Adnane. "OpenCL implementation of a SLAM system on an SoC-FPGA." Journal of Systems Architecture 111 (December 2020): 101825. http://dx.doi.org/10.1016/j.sysarc.2020.101825.

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Monthe, Valery Marcial, Laurent Nana, and Georges Edouard Kouamou. "A Model-Based Approach for Common Representation and Description of Robotics Software Architectures." Applied Sciences 12, no. 6 (March 15, 2022): 2982. http://dx.doi.org/10.3390/app12062982.

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Unlike conventional software, robotic software suffers from a lack of methods and processes that could systematize and facilitate development. Thus, the application of software engineering techniques is at the heart of current issues in robotics. The work presented in this paper aims to facilitate the development of robotic software and to facilitate communication between experts in the field through the use of software engineering techniques and methods. It proposes RsaML (Robotic Software Architecture Modeling Language), a Domain Specific Modeling Language (DSML) dedicated to robotics, which takes into account the different categories of robotic software architectures and makes it possible to describe the latter independently from the implementation platform. The conceptual model defining the terminology and the hierarchy of concepts used for the description and representation of robotic software architectures in RsaML are presented in this article. RsaML is defined through a meta-model which represents the abstract syntax of the language. The real-time properties of robotic software architectures are identified and included in the meta-model. The use of RsaML is illustrated through several experimental scenarios of the language: the definition of a robotic system and the description of its software architecture, the verification of the semantics of a robotic software architecture, and the modeling of a robotic system whose software architecture does not belong to the usual categories. The support tool used for implementations and experimentation is Eclipse Modeling Framework (EMF). The results of experimentation showed good working of the proposed solution and made it possible to validate the main concepts of the RsaML language.

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Álvarez - Gutiérrez, Edwin Leonel, and Fabián Rolando Jiménez - López. "Global Map Generation and SLAM using LiDAR and Stereo Camera for tracking motion of Mobile Robot." ITECKNE 16, no. 2 (December 16, 2019): 58–70. http://dx.doi.org/10.15332/iteckne.v16i2.2357.

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One of the topics of greatest attention in mobile robotics is related to the location and mapping of a robot in a given environment and the other, associated with the selection of the devices or sensors necessary to acquire as much external information as possible for the generation of a global map. The purpose of this article is to propose the integration between a caterpillar-type land mobile robot, SLAM tasks with LiDAR devices and the use of stereo vision through the ZED camera for the generation of a 2D global map and the tracking of the movement of the mobile robot using the MATLAB® software. The experiment consists of performing different detection tests to determine distances and track the position of mobile robot in a structured environment indoors, to observe the behavior of the mobile platform and determine the error in the measurements. The results obtained show that the integrated devices satisfactorily fulfill the tasks established in controlled conditions and in indoor environments, obtaining error percentages lower than 1 and 4% for the case of the LiDAR and the ZED camera respectively. An alternative was developed that solves one of the most common problems of mobile robotics in recent years and, additionally, this solution allows the possibility of merging other types of sensors such as inertial systems, encoders, GPS, among others, in order to improve the applications in the area and the quality of the information acquired from abroad.

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Fukuda, Toshio, and Takemasa Arakawa. "Computational intelligence in robotics and automation." Computer Standards & Interfaces 21, no. 2 (June 1999): 130. http://dx.doi.org/10.1016/s0920-5489(99)92042-1.

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28

Scypinski, Stephen, Theodore Sadlowski, and John Baiano. "Relocating and reestablishing a robotics laboratory." Computer Standards & Interfaces 21, no. 2 (June 1999): 130. http://dx.doi.org/10.1016/s0920-5489(99)92043-3.

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Schumny, Harald. "Computer architectures for robotics and automation." Computer Standards & Interfaces 7, no. 4 (January 1988): 395. http://dx.doi.org/10.1016/0920-5489(88)90029-3.

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Mueggler, Elias, Henri Rebecq, Guillermo Gallego, Tobi Delbruck, and Davide Scaramuzza. "The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM." International Journal of Robotics Research 36, no. 2 (February 2017): 142–49. http://dx.doi.org/10.1177/0278364917691115.

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New vision sensors, such as the dynamic and active-pixel vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array. These sensors have great potential for high-speed robotics and computer vision because they allow us to combine the benefits of conventional cameras with those of event-based sensors: low latency, high temporal resolution, and very high dynamic range. However, new algorithms are required to exploit the sensor characteristics and cope with its unconventional output, which consists of a stream of asynchronous brightness changes (called “events”) and synchronous grayscale frames. For this purpose, we present and release a collection of datasets captured with a DAVIS in a variety of synthetic and real environments, which we hope will motivate research on new algorithms for high-speed and high-dynamic-range robotics and computer-vision applications. In addition to global-shutter intensity images and asynchronous events, we provide inertial measurements and ground-truth camera poses from a motion-capture system. The latter allows comparing the pose accuracy of ego-motion estimation algorithms quantitatively. All the data are released both as standard text files and binary files (i.e. rosbag). This paper provides an overview of the available data and describes a simulator that we release open-source to create synthetic event-camera data.

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Becker, L. B., E. Nett, S. Schemmer, and M. Gergeleit. "Robust scheduling in team-robotics." Journal of Systems and Software 77, no. 1 (July 2005): 3–16. http://dx.doi.org/10.1016/j.jss.2003.12.035.

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Li, Xiuzhi, Wen Wang, Jiahao Chen, and Xiangyin Zhang. "DR-SLAM: drift rejection SLAM with Manhattan regularity for indoor environments." Advanced Robotics 36, no. 20 (October 18, 2022): 1049–59. http://dx.doi.org/10.1080/01691864.2022.2129032.

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Kalisperakis, I., T. Mandilaras, A. El Saer, P. Stamatopoulou, C. Stentoumis, S. Bourou, and L. Grammatikopoulos. "A MODULAR MOBILE MAPPING PLATFORM FOR COMPLEX INDOOR AND OUTDOOR ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 243–50. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-243-2020.

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Abstract. In this work we present the development of a prototype, mobile mapping platform with modular design and architecture that can be suitably modified to address effectively both outdoors and indoors environments. Our system is built on the Robotics Operation System (ROS) and utilizes multiple sensors to capture images, pointclouds and 3D motion trajectories. These include synchronized cameras with wide angle lenses, a lidar sensor, a GPS/IMU unit and a tracking optical sensor. We report on the individual components of the platform, it’s architecture, the integration and the calibration of its components, the fusion of all recorded data and provide initial 3D reconstruction results. The processing algorithms are based on existing implementations of SLAM (Simultaneous Localisation and Mapping) methods combined with SfM (Structure-from-Motion) for optimal estimations of orientations and 3D pointclouds. The scope of this work, which is part of an ongoing H2020 program, is to digitize the physical world, collect relevant spatial data and make digital copies available to experts and public for covering a wide range of needs; remote access and viewing, process, design, use in VR etc.

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Panayiotou, Konstantinos, Emmanouil Tsardoulias, Christoforos Zolotas, Andreas L. Symeonidis, and Loukas Petrou. "A Framework for Rapid Robotic Application Development for Citizen Developers." Software 1, no. 1 (March 3, 2022): 53–79. http://dx.doi.org/10.3390/software1010004.

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It is common knowledge among computer scientists and software engineers that ”building robotics systems is hard”: it includes applied and specialized knowledge from various scientific fields, such as mechanical, electrical and computer engineering, computer science and physics, among others. To expedite the development of robots, a significant number of robotics-oriented middleware solutions and frameworks exist that provide high-level functionality for the implementation of the in-robot software stack, such as ready-to-use algorithms and sensor/actuator drivers. While the aforementioned focus is on the implementation of the core functionalities and control layer of robots, these specialized tools still require extensive training, while not providing the envisaged freedom in design choices. In this paper, we discuss most of the robotics software development methodologies and frameworks, analyze the way robotics applications are built and propose a new resource-oriented architecture towards the rapid development of robot-agnostic applications. The contribution of our work is a methodology and a model-based middleware that can be used to provide remote robot-agnostic interfaces. Such interfaces may support robotics application development from citizen developers by reducing hand-coding and technical knowledge requirements. This way, non-robotics experts will be able to integrate and use robotics in a wide range of application domains, such as healthcare, home assistance, home automation and cyber–physical systems in general.

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Hexmoor, Henry, and David Kortenkamp. "Issues on building software for hardware agents." Knowledge Engineering Review 10, no. 3 (September 1995): 301–4. http://dx.doi.org/10.1017/s0269888900007499.

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James Albus states that “an architecture is a description of how a system is constructed from basic components and how those components fit together to form the whole” (Albus, 1995). A software architecture for physical agents reflects the organising principles that its designers have learned from many prior experiences in building such agents. Architectures that have been proposed for physical agents have differed greatly—from subsumption (Brooks, 1986) to Soar (Laird et al., 1987). However, a surprising consensus about architectures is beginning to emerge within the small community of researchers applying artificial intelligence to robotics. The consensus is that a multi- layer, hierarchical architecture is necessary. In particular, the community is moving towards a three-layered architecture. The lowest layer is a reactive control system inspired by subsumption (Brooks, 1986). The top layer is a traditional symbolic planning and modelling system. The middle layer is the key; it serves as a “differential” between the short-range reaction and long-range reasoning.

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Tschopp, Florian, Michael Riner, Marius Fehr, Lukas Bernreiter, Fadri Furrer, Tonci Novkovic, Andreas Pfrunder, Cesar Cadena, Roland Siegwart, and Juan Nieto. "VersaVIS—An Open Versatile Multi-Camera Visual-Inertial Sensor Suite." Sensors 20, no. 5 (March 6, 2020): 1439. http://dx.doi.org/10.3390/s20051439.

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Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as an inertial measurement unit (IMU) can boost robustness and accuracy. However, for a tight sensor fusion, accurate time synchronization of the sensors is often crucial. Changing exposure times, internal sensor filtering, multiple clock sources and unpredictable delays from operation system scheduling and data transfer can make sensor synchronization challenging. In this paper, we present VersaVIS, an Open Versatile Multi-Camera Visual-Inertial Sensor Suite aimed to be an efficient research platform for easy deployment, integration and extension for many mobile robotic applications. VersaVIS provides a complete, open-source hardware, firmware and software bundle to perform time synchronization of multiple cameras with an IMU featuring exposure compensation, host clock translation and independent and stereo camera triggering. The sensor suite supports a wide range of cameras and IMUs to match the requirements of the application. The synchronization accuracy of the framework is evaluated on multiple experiments achieving timing accuracy of less than 1 ms . Furthermore, the applicability and versatility of the sensor suite is demonstrated in multiple applications including visual-inertial SLAM, multi-camera applications, multi-modal mapping, reconstruction and object based mapping.

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Weinberg, Jerry B., William W. White, Cem Karacal, George Engel, and Ai-Ping Hu. "Multidisciplinary teamwork in a robotics course." ACM SIGCSE Bulletin 37, no. 1 (February 23, 2005): 446–50. http://dx.doi.org/10.1145/1047124.1047488.

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Aladem, Mohamed, and Samir Rawashdeh. "Lightweight Visual Odometry for Autonomous Mobile Robots." Sensors 18, no. 9 (August 28, 2018): 2837. http://dx.doi.org/10.3390/s18092837.

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Vision-based motion estimation is an effective means for mobile robot localization and is often used in conjunction with other sensors for navigation and path planning. This paper presents a low-overhead real-time ego-motion estimation (visual odometry) system based on either a stereo or RGB-D sensor. The algorithm’s accuracy outperforms typical frame-to-frame approaches by maintaining a limited local map, while requiring significantly less memory and computational power in contrast to using global maps common in full visual SLAM methods. The algorithm is evaluated on common publicly available datasets that span different use-cases and performance is compared to other comparable open-source systems in terms of accuracy, frame rate and memory requirements. This paper accompanies the release of the source code as a modular software package for the robotics community compatible with the Robot Operating System (ROS).

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Berg, John L. "Robotics, artificial intelligence, productivity: US-Japan concomitant coalitions." Computer Standards & Interfaces 7, no. 3 (January 1988): 329–30. http://dx.doi.org/10.1016/0920-5489(88)90099-2.

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Bedkowski, Janusz, Timo Röhling, Frank Hoeller, Dirk Shulz, and Frank E. Schneider. "Benchmark of 6D SLAM (6D Simultaneous Localisation and Mapping) Algorithms with Robotic Mobile Mapping Systems." Foundations of Computing and Decision Sciences 42, no. 3 (September 1, 2017): 275–95. http://dx.doi.org/10.1515/fcds-2017-0014.

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AbstractThis work concerns the study of 6DSLAM algorithms with an application of robotic mobile mapping systems. The architecture of the 6DSLAM algorithm is designed for evaluation of different data registration strategies. The algorithm is composed of the iterative registration component, thus ICP (Iterative Closest Point), ICP (point to projection), ICP with semantic discrimination of points, LS3D (Least Square Surface Matching), NDT (Normal Distribution Transform) can be chosen. Loop closing is based on LUM and LS3D. The main research goal was to investigate the semantic discrimination of measured points that improve the accuracy of final map especially in demanding scenarios such as multi-level maps (e.g., climbing stairs). The parallel programming based nearest neighborhood search implementation such as point to point, point to projection, semantic discrimination of points is used. The 6DSLAM framework is based on modified 3DTK and PCL open source libraries and parallel programming techniques using NVIDIA CUDA. The paper shows experiments that are demonstrating advantages of proposed approach in relation to practical applications. The major added value of presented research is the qualitative and quantitative evaluation based on realistic scenarios including ground truth data obtained by geodetic survey. The research novelty looking from mobile robotics is the evaluation of LS3D algorithm well known in geodesy.

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Lienen, Christian, and Marco Platzner. "Design of Distributed Reconfigurable Robotics Systems with ReconROS." ACM Transactions on Reconfigurable Technology and Systems 15, no. 3 (September 30, 2022): 1–20. http://dx.doi.org/10.1145/3494571.

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Robotics applications process large amounts of data in real time and require compute platforms that provide high performance and energy efficiency. FPGAs are well suited for many of these applications, but there is a reluctance in the robotics community to use hardware acceleration due to increased design complexity and a lack of consistent programming models across the software/hardware boundary. In this article, we present ReconROS , a framework that integrates the widely used robot operating system (ROS) with ReconOS, which features multithreaded programming of hardware and software threads for reconfigurable computers. This unique combination gives ROS 2 developers the flexibility to transparently accelerate parts of their robotics applications in hardware. We elaborate on the architecture and the design flow for ReconROS and report on a set of experiments that underline the feasibility and flexibility of our approach.

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Karalekas, Georgios, Stavros Vologiannidis, and John Kalomiros. "EUROPA: A Case Study for Teaching Sensors, Data Acquisition and Robotics via a ROS-Based Educational Robot." Sensors 20, no. 9 (April 27, 2020): 2469. http://dx.doi.org/10.3390/s20092469.

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Robots have become a popular educational tool in secondary education, introducing scientific, technological, engineering and mathematical concepts to students all around the globe. In this paper EUROPA, an extensible, open software and open hardware robotic platform is presented focusing on teaching physics, sensors, data acquisition and robotics. EUROPA’s software infrastructure is based οn Robot Operating System (ROS). It includes easy to use interfaces for robot control and interaction with users and thus can easily be incorporated in Science, Technology, Engineering and Mathematics (STEM) and robotics classes. EUROPA was designed taking into account current trends in educational robotics. An overview of widespread robotic platforms is presented, documenting several critical parameters of interest such as their architecture, sensors, actuators and controllers, their approximate cost, etc. Finally, an introductory STEM curriculum developed for EUROPA and applied in a class of high school students is presented.

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Chioreanu, Adrian, Stelian Brad, and Cosmin Ioanes. "Vision on Intelligent Management of Industrial Robotics Systems." Applied Mechanics and Materials 162 (March 2012): 368–77. http://dx.doi.org/10.4028/www.scientific.net/amm.162.368.

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Based on Future Internet and ITIL, cutting edge concepts and approaches related to software service systems in distributed architectures for managing information and processes in industrial robot platforms are introduced. A new approach in defining the business relation for entities that have various interests related to industrial robots, as well as tools that support the new business approach are also identified in this paper. Further the architecture of a prototype platform designed around those concepts is presented.

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Oliveira, Eugénio, R. Camacho, and C. Ramos. "A multi-agent environment in robotics." Robotica 9, no. 4 (December 1991): 431–40. http://dx.doi.org/10.1017/s0263574700000618.

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SUMMARYThe use of Multi-Agent Systems as a Distributed AI paradigm for Robotics is the principal aim of our present work. In this paper we consider the needed concepts and a suitable architecture for a set of Agents in order to make it possible for them to cooperate in solving non-trivial tasks.Agents are sets of different software modules, each one implementing a function required for cooperation. A Monitor, an Acquaintance and Self-knowledge Modules, an Agenda and an Input queue, on the top of each Intelligent System, are fundamental modules that guarantee the process of cooperation, while the overall aim is devoted to the community of cooperative Agents. These Agents, which our testbed concerns, include Vision, Planner, World Model and the Robot itself.

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Yuh, J., and M. West. "Underwater robotics." Advanced Robotics 15, no. 5 (January 2001): 609–39. http://dx.doi.org/10.1163/156855301317033595.

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Klassner, Frank. "Enhancing lisp instruction with RCXLisp and robotics." ACM SIGCSE Bulletin 36, no. 1 (March 2004): 214–18. http://dx.doi.org/10.1145/1028174.971377.

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Steidley, Carl W. "Robotics: a closer look at microprocessor systems." ACM SIGCSE Bulletin 23, no. 1 (March 1991): 265–72. http://dx.doi.org/10.1145/107005.107063.

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Gips, James. "A robotics course using hero I robots." ACM SIGCSE Bulletin 18, no. 4 (December 1986): 65–68. http://dx.doi.org/10.1145/15003.15017.

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Kamarudin, Kamarulzaman, Ali Yeon Md Shakaff, Victor Hernandez Bennetts, Syed Muhammad Mamduh, Ammar Zakaria, Retnam Visvanathan, Ahmad Shakaff Ali Yeon, and Latifah Munirah Kamarudin. "Integrating SLAM and gas distribution mapping (SLAM-GDM) for real-time gas source localization." Advanced Robotics 32, no. 17 (September 2, 2018): 903–17. http://dx.doi.org/10.1080/01691864.2018.1516568.

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Mishra, Bhavyansh, Robert Griffin, and Hakki Erhan Sevil. "Modelling Software Architecture for Visual Simultaneous Localization and Mapping." Automation 2, no. 2 (April 2, 2021): 48–61. http://dx.doi.org/10.3390/automation2020003.

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Visual simultaneous localization and mapping (VSLAM) is an essential technique used in areas such as robotics and augmented reality for pose estimation and 3D mapping. Research on VSLAM using both monocular and stereo cameras has grown significantly over the last two decades. There is, therefore, a need for emphasis on a comprehensive review of the evolving architecture of such algorithms in the literature. Although VSLAM algorithm pipelines share similar mathematical backbones, their implementations are individualized and the ad hoc nature of the interfacing between different modules of VSLAM pipelines complicates code reuseability and maintenance. This paper presents a software model for core components of VSLAM implementations and interfaces that govern data flow between them while also attempting to preserve the elements that offer performance improvements over the evolution of VSLAM architectures. The framework presented in this paper employs principles from model-driven engineering (MDE), which are used extensively in the development of large and complicated software systems. The presented VSLAM framework will assist researchers in improving the performance of individual modules of VSLAM while not having to spend time on system integration of those modules into VSLAM pipelines.

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