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Academic literature on the topic 'ENVIRONMENT FORCE ESTIMATION'

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Published: 11 September 2023

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Journal articles on the topic "ENVIRONMENT FORCE ESTIMATION"

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Mallapragada, Vishnu, Duygun Erol, and Nilanjan Sarkar. "A New Method of Force Control for Unknown Environments." International Journal of Advanced Robotic Systems 4, no. 3 (September 1, 2007): 34. http://dx.doi.org/10.5772/5684.

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Current robotic systems are expected to interact with unknown environment where controlling the interaction forces becomes an important issue. We propose a new control technique for force control on unknown environments that tunes the force controller based on online estimation of the environment parameters. However, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling force controller to track the desired force by adjusting control gains such that error in parameter estimation can be accommodated. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed.
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Körding, Konrad P., Shih-pi Ku, and Daniel M. Wolpert. "Bayesian Integration in Force Estimation." Journal of Neurophysiology 92, no. 5 (November 2004): 3161–65. http://dx.doi.org/10.1152/jn.00275.2004.

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When we interact with objects in the world, the forces we exert are finely tuned to the dynamics of the situation. As our sensors do not provide perfect knowledge about the environment, a key problem is how to estimate the appropriate forces. Two sources of information can be used to generate such an estimate: sensory inputs about the object and knowledge about previously experienced objects, termed prior information. Bayesian integration defines the way in which these two sources of information should be combined to produce an optimal estimate. To investigate whether subjects use such a strategy in force estimation, we designed a novel sensorimotor estimation task. We controlled the distribution of forces experienced over the course of an experiment thereby defining the prior. We show that subjects integrate sensory information with their prior experience to generate an estimate. Moreover, subjects could learn different prior distributions. These results suggest that the CNS uses Bayesian models when estimating force requirements.
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Roveda, Loris, and Dario Piga. "Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks." Autonomous Robots 45, no. 3 (March 2021): 371–88. http://dx.doi.org/10.1007/s10514-021-09970-z.

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AbstractIndustrial robots are increasingly used to perform tasks requiring an interaction with the surrounding environment (e.g., assembly tasks). Such environments are usually (partially) unknown to the robot, requiring the implemented controllers to suitably react to the established interaction. Standard controllers require force/torque measurements to close the loop. However, most of the industrial manipulators do not have embedded force/torque sensor(s) and such integration results in additional costs and implementation effort. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper. Relying on sensorless Cartesian impedance control, two Extended Kalman Filters (EKF) are proposed: an EKF for interaction force estimation and an EKF for environment stiffness estimation. Exploiting such estimations, a control architecture is proposed to implement a sensorless force loop (exploiting the provided estimated force) with adaptive Cartesian impedance control and coupling dynamics compensation (exploiting the provided estimated environment stiffness). The described approach has been validated in both simulations and experiments. A Franka EMIKA panda robot has been used. A probing task involving different materials (i.e., with different - unknown - stiffness properties) has been considered to show the capabilities of the developed EKFs (able to converge with limited errors) and control tuning (preserving stability). Additionally, a polishing-like task and an assembly task have been implemented to show the achieved performance of the proposed methodology.
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Shushtari, Mohammad, and Arash Arami. "Human–Exoskeleton Interaction Force Estimation in Indego Exoskeleton." Robotics 12, no. 3 (May 1, 2023): 66. http://dx.doi.org/10.3390/robotics12030066.

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Accurate interaction force estimation can play an important role in optimizing human–robot interaction in an exoskeleton. In this work, we propose a novel approach for the system identification of exoskeleton dynamics in the presence of interaction forces as a whole multibody system without imposing any constraints on the exoskeleton dynamics. We hung the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton–environment interaction force. Several structures of neural networks were trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time–delays could obtain a sufficiently accurate estimation of the interaction force, resulting in an RMSE of 1.23 on Z–normalized applied torques and an adjusted R2 of 0.89.
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Ohishi, Kiyoshi, Masaru Miyazaki, and Masahiro Fujita. "Hybrid Position and Force Control Without Force Sensor." Journal of Robotics and Mechatronics 8, no. 3 (June 20, 1996): 226–34. http://dx.doi.org/10.20965/jrm.1996.p0226.

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Generally, hybrid control is realized by sensor signal feedback of position and force. However, some robot manipulators do not have a force sensor due to the environment. Moreover, a precise force sensor is very expensive. In order to overcome these problems, we propose the estimation system of reaction force without using a force sensor. This system consists of the torque observer and the inverse dynamics calculation. Using both this force estimation system and <I>H</I>∞ acceleration controller which is based on <I>H</I>∞ control theory, it takes into account the frequency characteristics of both sensor noise effect and disturbance rejection. The experimental results in this paper illustrate the fine hybrid control of the three tested degrees-of-freedom DD robot manipulator without force sensor.
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Azimifar, Farhad, Saman Ahmadkhosravi Rozi, Ahmad Saleh, and Iman Afyouni. "Transparency performance improvement for multi-master multi-slave teleoperation systems with external force estimation." Transactions of the Institute of Measurement and Control 40, no. 13 (December 7, 2017): 3851–59. http://dx.doi.org/10.1177/0142331217740178.

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Cooperative teleoperation combines two traditional areas of robotics, that is, teleoperation and collaborative manipulation. Cooperative telerobotic systems consist of multiple pairs of master and slave robotic manipulators operating in a shared environment. The most common control frameworks for nonlinear systems, that is, Proportional Derivative (PD) controllers, possess considerable deficiency in contact motion. In this paper, a novel control scheme is proposed for a nonlinear bilateral cooperative teleoperation system with time delay. In addition to position and velocity signals, force signals are employed in the control strategy. This modification significantly enhances the poor transparency when the slave robots are in collision with the environment. To cope with external forces measurement, a modified force estimation algorithm is proposed to estimate human and environment forces. The closed loop stability of the nonlinear cooperative teleoperation system with the proposed control scheme is investigated using the Lyapunov theory. The main achievement of this research is the stability of the closed loop cooperative teleoperation system in the presence of estimated operator and environmental forces. In addition, it is theoretically and experimentally proved that force reflection occurs and transparency is improved at the same time. Experimental results demonstrate the efficiency of the presented control strategy in free motion as well as when the slave robots are in contact with the environment.
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Nagpal, Neelu, Bharat Bhushan, and Vijyant Agarwal. "Estimation of stochastic environment force for master–slave robotic system." Sādhanā 42, no. 6 (April 26, 2017): 889–99. http://dx.doi.org/10.1007/s12046-017-0643-7.

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Trębiński, Radosław, Ryszard Woźniak, Damian Szupieńko, and Bartosz Fikus. "Estimation of Priming Mixture Force." Energies 15, no. 16 (August 17, 2022): 5952. http://dx.doi.org/10.3390/en15165952.

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This paper presents the results of the estimation of the priming mixture force for primers used in 12.7 mm ammunition. The method of estimation is based on the results of pressure measurements in a closed chamber into which the products of the combustion of the priming mixture flowed. The capacity of the chamber was changed by inserting sleeves of various volumes. Another estimation of the force value was performed using the results of earlier investigations in which the chamber was filled with glass balls. The determined values of the force were compared with the values estimated based on the accessible literature data. The obtained estimations of the force value are of the same order of magnitude as the force value of black powder. This justifies the use of black powder characteristics for the assessment of the thermodynamic properties of priming mixture combustion products in interior ballistics calculations. The time of action of the investigated primer was determined using the optical recording of the outflow of the priming mixture combustion products into an open space. To facilitate the interpretation of the results of the experiments, a theoretical model was used.
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Kallu, Karam Dad, Amad Zafar, Muhammad Umair Ali, Shahzad Ahmed, and Min Cheol Lee. "Robust Controller for Pursuing Trajectory and Force Estimations of a Bilateral Tele-Operated Hydraulic Manipulator." Remote Sensing 13, no. 9 (April 23, 2021): 1648. http://dx.doi.org/10.3390/rs13091648.

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In hazardous/emergency situations, public safety is of the utmost concern. In areas where human access is not possible or is restricted due to hazardous situations, a system or robot that can be distantly controlled is mandatory. There are many applications in which force cannot be applied directly while using physical sensors. Therefore, in this research, a robust controller for pursuing trajectory and force estimations while deprived of any signals or sensors for bilateral tele-operation of a hydraulic manipulator is suggested to handle these hazardous, emergency circumstances. A terminal sliding control with a sliding perturbation observer (TSMCSPO) is considered as the robust controller for a coupled leader and hydraulic follower system. The ultimate use of this controller is as a sliding perturbation observer (SPO) that can estimate the reaction force without any physical force sensors. Robust and perfect position tracking is attained with terminal sliding mode control (TSMC) in addition to control of the hydraulic follower manipulator. The force estimation and pursuing trajectory for the leader–follower system is built upon a bilateral tele-operation control approach. The difference between the reaction forces (caused by the remote environment) and the operating forces (applied by the human operator) required the involvement of an impedance model. The impedance model is implemented in the leader manipulator to provide human operators with an actual sense of the reaction force while the manipulator connects with the remote environment. A camera is used to ensure the safety of the workplace through visual feedback. The experimental results showed that the controller was robust at pursuing trajectory and force estimations for the bilateral tele-operation control of a hydraulic manipulator.
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Ferretti, G., C. Maffezzoni, G. Magnani, and P. Rocco. "Joint Stiffness Estimation Based on Force Sensor Measurements in Industrial Manipulators." Journal of Dynamic Systems, Measurement, and Control 116, no. 1 (March 1, 1994): 163–67. http://dx.doi.org/10.1115/1.2900673.

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The problem of estimating the stiffness constants of the joints in industrial manipulators is addressed in this paper. It is shown that the model of the robot constrained by a rigid environment yields a simple relationship between variations of the motor coordinates and the forces arising at the contact with the environment. By exploiting the measurements of the motor positions sensors and of a force sensor located at the end effector a method is proposed to simply compute good estimates of the stiffness constants. Experiments have been made on the industrial robot SMART and the results are given and discussed.
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Dissertations / Theses on the topic "ENVIRONMENT FORCE ESTIMATION"

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Essebbar, Abderrahman. "Séparation paramétrique des ondes en sismique." Phd thesis, Grenoble INPG, 1992. http://tel.archives-ouvertes.fr/tel-00785644.

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Dans cette étude, nous nous intéressons à la séparation des ondes sismiques, traitement principal conditionnant toute interprétation physique des données. En première partie, les méthodes de séparation non paramétriques (Matrice spectrale, Transformée de Karhunen-Loève et Filtrage FK) sont étudiées. La limitation de ces méthodes nous a conduit à utiliser l'approche paramétrique. Cette approche fait apparaître une modélisation qui permet de tenir compte des divers types d'ondes sismiques. La séparation paramétrique des ondes utilise l'estimateur du maximum de vraisemblance. Elle est réalisée en estimant les différents paramètres (lenteur apparente, amplitude, forme de l'onde, phase et angle d'incidence) caractérisant chaque onde. Les différentes méthodes d'estimation ainsi que les limites et les performances de la séparation paramétrique sont étudiées en deuxième partie. Les résultats de cette étude sont appliqués, en dernière partie, au traitement des signaux sismiques de puits issus d'une expérimentation ainsi qu'à des ondes dispersives de sismique de, surface.
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NAGPAL, NEELU. "ENVIRONMENT FORCE ESTIMATION WITH STOCHASTIC NOISE AND CONTROL FOR ROBOTICS." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16742.

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The proposed work entitled “Environment Force Estimation with Stochastic Noise and Control for Robotics” focuses on estimation of state vector and controller’s parameters and control of a robot in the presence of noise. Also, environment force is estimated when robot has interaction with randomly structured environment. In the present work, two typical issues are investigated for the robotic system. The first one deals with the noise present in the system. Noise is wiped out from the output measurement by utilizing state-observer which in turn, feeds the estimated state to a controller in spite of noisy state. Thus, any further randomness is restricted and focus of the work is to design, implement and test the optimal state-observer-based controller. It aims for trajectory control of the state of an n-link robot to track the desired trajectory in the presence of stochastic noise. The novel feature of the present control algorithm is based on Itˆ o0s stochastic calculus. It is used for the minimization of the conditional expectation of the instantaneous tracking error energy differential with respect to the feedback matrix. This instantaneous minimization results in an adaptive action of the controller. At the same time, it also maintains the energy constraints in the feedback coefficients to avoid actuator saturation. This enables to validate the real-time implementation of state-observer-based controller by an experimental set up of “Phantom Omni Bundle” robot manipulator. Furthermore, the sensitivity analysis of controller gain variation and parameter variation on the error process is performed, and the robustness of the system is assured by the bounded errors. Another important and relevant issue is that when noise appears in the form of environmental torque and randomness becomes a part of the closed-loop system and makes the dynamics of the nonlinear system ‘stochastic’. Utilizing the sample data of noisy measurement of joint position, the ‘likelihood function’ of tracking error is computed. Minimization of this function estimates the unknown controller gain parameters. The trajectory of stochastic environment force is also computed iii from the estimates of controller gain parameters. Subsequently, the performance of estimation is determined using convergence analysis and imposing lower bound on the variance of estimation errors. In the present study, both issues are addressed for a nonlinear dynamical system in a stochastic scenario. Controllers are designed based on estimation without using any velocity sensor or force sensor.
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Hacksel, Peter J. "Observer based velocity and environment force estimation for rigid body control." Thesis, 1993. http://hdl.handle.net/2429/1778.

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Issues pertaining to the control of a rigid body are considered in this work. A magnetically levitated robotic wrist is here modelled as a rigid body subjected to both control and environment forces. All the algorithms presented here were implemented on the Maglev wrist for experimental verification. A good inertial model of the rigid body was needed for the estimation and control work in this work; a least squares identification procedure, found in the literature, was implemented for this purpose. Algorithms are developed for obtaining dynamic environment force and torque estimates from position errors in a velocity observer. Obtaining torque estimates from a nonlinear velocity observer is achieved by using the linear force observer as an analogue. Stability of the torque observer to a constant environment torque is proven for the one dimensional case only. Simulation and experiments are used to verify the stability in the three dimensional case. Environment force/torque measurements, alone useful for control purposes, are also used to correct a velocity observer. The resulting corrected observer design gives low noise velocity estimates and is robust in that it is not sensitive to errors caused by interaction with the environment. As a demonstration of the merit of the observer based work, a remote center of compliance controller is implemented. An inertial model is needed to provide feedforward that linearizes the dynamics to a. second order system. Corrected observer velocities are used in the feedforward and the derivative component of the control law. The linear dynamics about a remote center is verified by comparing the environment forces measured with the velocities observed.
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Books on the topic "ENVIRONMENT FORCE ESTIMATION"

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Financial management: Factors to consider in estimating environmental liabilities for removing hazardous materials in nuclear submarines and ships. Washington, D.C: The Office, 1997.

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Kelly, Phil. Defending Classical Geopolitics. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228637.013.279.

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Three successive parts are presented within this article, all intended to raise the visibility and show the utility of classical geopolitics as a deserving and separate international-relations model: (a) a common traditional definition, (b) relevant theories that correspond to that definition, and (c) applications of certain theories that will delve at some depth into three case studies (the Ukrainian shatterbelt, contemporary Turkish geopolitics, and a North American heartland).The placement of states, regions, and resources, as affecting international relations and foreign policies, defines classical geopolitics. This definition emphasizes the application of spatially composed unbiased theories that should bring insight into foreign-affairs events and policies. Specifically, a “model” contains theories that correspond to its description. A “theory” is a simple sentence of probability, with “A” happening to likely affect “B.” Importantly, models are passive; they merely hold theories. In contrast, theories possess their own titles and perform actively when taken from such models.Various methodological challenges are presented: (a) combining concepts with theories, (b) estimating probability for testing theories, (c) claiming the “scientific,” (d) accounting for determinism, (e) revealing a dynamic environment for geopolitics, (f) separating realism from geopolitics, and (g) drawing classical geopolitics away from the critical. Certain theories that are placed within the geopolitical model are examined next: (a) heartlands and rimlands, (b) land and sea power, (c) choke points and maritime lines of communication, (d) offshore balancing, (e) the Monroe doctrine, (f) balances of power, (g) checkerboards, (h) shatterbelts, (i) pan-regions, (j) influence spheres, (k) dependency, (l) buffer states, (m) organic borders, (n) imperial thesis, (o) borders/wars, (p) contagion, (q) irredentism, (r) demography, (s) fluvial laws, (t) petro-politics, and (u) catastrophic events in nature. Additional theories apply elsewhere in the article as well.Of the three case studies, the Ukrainian shatterbelt represents the sole contemporary geopolitical configuration of this type, a regional conflict coupling with a strategic rivalry. Here, partisans of the civil war between the eastern and the western sectors of the country have joined with the Russians against the Europeans and Americans, respectively. Next, Turkey’s pivotal location has afforded it both advantages and disadvantages, a topic discussed at some length earlier in the article. Its “zero-problems” strategy of seeking positive relations with neighbors has now been forced to change tactics, reflective of new forces within and beyond the country. Finally, a North American heartland compares nicely to Halford Mackinder’s earlier Eurasia heartland thesis, with the American perhaps proving more stable, wealthy, and enduring, based in large part on its stronger geopolitical features.
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Book chapters on the topic "ENVIRONMENT FORCE ESTIMATION"

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Schultz, Ryan A. "A Demonstration of Force Estimation and Regularization Methods for Multi-Shaker Testing." In Sensors and Instrumentation, Aircraft/Aerospace, Energy Harvesting & Dynamic Environments Testing, Volume 7, 229–43. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12676-6_21.

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Li, Hang, Jie Hou, and Xinmin Liu. "Estimation of the Electrostatic Repulsive Force among Charged Clay Particles in Aqueous Systems." In Molecular Environmental Soil Science at the Interfaces in the Earth’s Critical Zone, 81–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05297-2_25.

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Capaldi, Mark P. "Present-Day Migration in Southeast Asia: Evolution, Flows and Migration Dynamics." In IMISCOE Research Series, 1–19. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25748-3_1.

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AbstractThe proportion of people’s movement within Southeast Asia continues to rise with the UN estimating there are over ten million international migrants in the region. The causes of migration are varied and may be due to economic inequalities, environmental degradation, violent conflicts and other forms of human rights violations. Many of the richer countries in the region (where 96% of the region’s migrants are found) depend on human mobility to fill low-wage jobs in agriculture, tourism, construction, domestic help and their plight has been thrust into the spotlight by the COVID-19 pandemic. Forced, irregular and mixed migratory flows are all key trends in Southeast Asia. This chapter aims to explore the dynamics of these mixed migration flows by taking a theoretical approach to analysing migration in the region. The chapter concludes by assessing the effectiveness of existing policies and mechanisms in Southeast Asia in order to provide recommendations for a more rights-based regional approach to migration.
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Pichl, Lukáš, and Takuya Yamano. "Computer-Aided Management of Software Development in Small Companies." In Software Applications, 2379–90. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-060-8.ch140.

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This chapter focuses on the principles of management in software development projects and optimization tools for managerial decision making, especially in the environment of small IT companies. The management of software projects is specific by high requirements on qualified labor force, large importance of the human capital, low level of fixed costs, and highly fluctuating product demand. This yields a dynamic combinatorial problem for the management involving considerable risk factors. The key aspects addressed here are structuring of the project team, cost estimation, and error avoidance in the implementation phase of the project. Special emphasis is put on human resource and fault-tolerant management of the project cycle. Discrete faults and continuous stochastic inputs are used to test and evaluate project variants. We have developed an online simulation tool for this purpose that facilitates findings of optimal resource structures and creation of optimal network from task relations. General principles of software project management are presented along with the analysis of the software project simulation tool in a brief case study.
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Jiang, Lihua, and Mingcong Deng. "Support Vector Machine Based Mobile Robot Motion Control and Obstacle Avoidance." In Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, 223–51. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch008.

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Considering the noise effect during the navigation of a two wheeled mobile robot, SVM and LS-SVM based control schemes are discussed under the measured information with uncertainty, and in the different environments. The noise effect is defined as uncertainty in the measured data. One of them focuses on using a potential function and constructing a plane surface for avoiding the local minima in the static environments, where the controller is based on Lyapunov function candidate. Another one addresses to use a potential function and to define a new detouring virtual force for escaping from the local minima in the dynamic environments. Stability of the control system can be guaranteed. However, the motion control of the mobile robot would be affected by the noise effect. The SVM and LS-SVM for function estimation are used for estimating the parameter in the proposed controllers. With the estimated parameter, the noise effect during the navigation of the mobile robot can be reduced.
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Shmelova, Tetiana, and Yuliya Sikirda. "Applications of Decision-Support Systems in Sociotechnical Systems." In Unmanned Aerial Vehicles, 188–213. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8365-3.ch008.

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In this chapter, the authors present conceptual models of decision support systems (DSS) and Expert systems (ES) for Human-Operator (H-O) of Air Navigation System (ANS), such as air traffic controller (ATC) in flight emergencies, Unmanned Aerial Vehicles (UAV) operator, Safety Management System (SMS), etc. The authors made an analysis of the International civil aviation organization (ICAO) documents on risk assessment and the impact of the social environment on the aviation system. Automated system of pre-flight information preparation with intelligent module for support the decision making (DM) about aircraft departure are presented and program realization of systems are shown. The authors obtained algorithm of determining the optimal aerodrome for the forced landing of aircraft is provided. Expert systems of aviation enterprise's estimation were developed. Inhomogeneous factors of internal and external management environment of aviation enterprise were generalized using set-theoretical approach. This gave possibilities to define that the level of safety of aviation activity has the greatest influence among factors of internal environment and global economic situation – among factors of external environment. The authors demonstrate some interesting applications of DM in Socio-Technical Systems (STS). The DSS for H-O of ANS in the emergency situational were developed. Examples of DSS: DSS of ATC in the emergency situational; the flight dispatcher's DSS; DSS of UAV's operator, etc. In addition, the chapter presents some cases of DSS developed by the authors and colleagues at National Aviation University, Ukraine.
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Bircan, Tuba. "Remote Sensing Data for Migration Research." In Data Science for Migration and Mobility, 115–40. British Academy, 2022. http://dx.doi.org/10.5871/bacad/9780197267103.003.0006.

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With the rise of Big Data use, deployment of earth observation and remote sensing has gained popularity also for migration studies. Not only the impact of environmental factors, but also of conflict zones and disaster emergence for human mobility and migration can be investigated through analysing different types of remote sensing data by computational methods. In this chapter, after construing the essential concepts of remote sensing, sensors and satellite systems and highlighting the data content and access to publicly available remote sensing data products, we illustrate three application-specific show cases. These are on ethnic migration, environmentally induced human migration and armed conflict related forced migration from Uganda, Mexico, and Colombia, respectively. With this chapter, we documented that satellites are a high potential data source for deriving population estimations for at-risk-communities, displaced people, and refugee groups, for predicting forced migration flows, notably in the context of natural disasters, climate extremes and conflict zones; as well as for generating essential information to facilitate assistance and support for pre- and during-crisis/disaster resilience-building interventions. We conclude that further cooperation between scientists and practitioners is crucial to enhance the benefits and to address the challenges for developing human-rights compliant applications.
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Thrall, Grant Ian. "Conducting Real Estate Market Analysis." In Business Geography and New Real Estate Market Analysis. Oxford University Press, 2002. http://dx.doi.org/10.1093/oso/9780195076363.003.0007.

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This chapter establishes a general framework for conducting market analysis for all types of real estate. The subsequent chapters show how, with appropriate modifications, this general framework applies to specific real estate product types. The following chapters also include examples of the general approach introduced here. Four general steps must be included in all real estate market analysis. This chapter will progress through each of the four steps. First, a trade area, also known as a market area, must be established from which to draw the data for the real estate market analysis. Explanation is provided on how to delineate a trade area for the project, including how large the trade area is and the geographic delineation of its boundaries. Second, to evaluate the competitive position of the project, competing supply is estimated. Competing supply includes both current and projected supply within the trade area derived in the first step. To identify competitive projects, the market analyst must also determine what segment the real estate project is to compete in. Third, demand must be measured. Demand estimation includes the assembly and use of projections of economic, geographic, and social indicators that together influence the demand for a specific real estate project. Occasionally, data readily available from commercial data vendors are inadequate for specific types of real estate projects. In these circumstances, demand is estimated using primary research, including surveys and focus groups, as well as assembly of primary data. The fourth step is compiling the report and presenting the analysis to client. The report must reconcile the results of the foregoing three steps with the goals and needs of the client. The client may be an investor, a developer, a redevelopment agency, and so on. The objectives of the client might influence how the fundamental first three steps are interpreted. The market analysis report generally concludes with recommendations, as well as a description of the overall project within the wide context of the economic, geographic, and social forces that are shaping the urban built environment. The analyst draws conclusions, including projecting absorption rates and pricing recommendations.
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Dryfoos, Joy G. "Prevalence of School Failure and Dropping Out." In Adolescents at Risk. Oxford University Press, 1992. http://dx.doi.org/10.1093/oso/9780195072686.003.0009.

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In this chapter, we turn to the risk behavior that appears to underlie many of the problems addressed so far. Low achievement in school has been shown to be an important predictor of substance abuse, delinquency, and early sexual intercourse. And as we will see, not only are many of the antecedents of poor school performance the same as those for other problem behaviors, so are the consequences. Moreover, low academic achievement is both a predictor and a consequence of other kinds of risk behavior, as well as being a problem in itself. Understanding the epidemiology of school failure and dropping out is fundamental to this book’s argument: that high-risk behaviors are interrelated and, therefore, interventions must be comprehensive. School failure is a process rather than a single risk event. A young person initiates hard drug use or has early unprotected sexual intercourse or first commits a delinquent act at a specific time and place. Usually these actions are voluntary and follow a personal decision (although they are heavily influenced by the social environment). Low achievement results from an array of forces, many of which are outside the control of the child. The quality of the school is, of course, a major factor, as are the actual classroom practices and attitudes of the teacher. Estimates of the risk of other problem behaviors can be projected based on individual characteristics. Children with certain attributes are more likely than others to get involved in certain behaviors. This is not necessarily the case for estimating the risk of school failure since the probabilities are conditioned by both individual characteristics and the quality of the school. Children from disadvantaged households have been shown to succeed in excellent schools, while some schools are so inadequate that success is an exception. Unlike the other behaviors, risk of educational failure is measured routinely for almost all children at frequent intervals. Report cards inform children about their progress and, in aggregate, these marks produce a grade point average for each student.
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Conference papers on the topic "ENVIRONMENT FORCE ESTIMATION"

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Bhattacharjee, Tapomayukh, Hyoung Il Son, and Doo Yong Lee. "Haptic control with environment force estimation for telesurgery." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4649895.

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Hansen, Thomas, Claus T. Henningsen, Jens J. M. Nielsen, Rasmus Pedersen, John Schwensen, Senthuran Sivabalan, Jesper A. Larsen, and John Leth. "Implementing force-feedback in a telesurgery environment, using parameter estimation." In 2012 IEEE International Conference on Control Applications (CCA). IEEE, 2012. http://dx.doi.org/10.1109/cca.2012.6402708.

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Roveda, Loris, and Dario Piga. "Interaction Force Computation Exploiting Environment Stiffness Estimation for Sensorless Robot Applications." In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). IEEE, 2020. http://dx.doi.org/10.1109/metroind4.0iot48571.2020.9138189.

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Khabbaz, Faezeh Heydari, Andrew Goldenberg, and James Drake. "An adaptive force reflective teleoperation control method using online environment impedance estimation." In 2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS). IEEE, 2014. http://dx.doi.org/10.1109/riiss.2014.7009167.

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Zheng, M., and J. Yu. "A Modified Approach for Drawing Force Estimation of Bi-metallic Composite Pipe Forming." In 6th International Conference on Mechatronics, Materials, Biotechnology and Environment (ICMMBE 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icmmbe-16.2016.53.

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Camassa, Domenico, Antonio Curri, Aguinaldo Fraddosio, and Mario Daniele Piccioni. "In-situ estimation of axial force in tie rods of masonry structures by radar interferometry." In 2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv). IEEE, 2023. http://dx.doi.org/10.1109/metrolivenv56897.2023.10164069.

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Coutinho, Fernanda, and Rui Cortesao. "Comparison of position and force-based techniques for environment stiffness estimation in robotic tasks." In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012). IEEE, 2012. http://dx.doi.org/10.1109/iros.2012.6386161.

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Roveda, Loris, Federico Vicentini, Nicola Pedrocchi, Lorenzo Molinari Tosatti, and Francesco Braghin. "Development of Impedance Control Based Strategies for Light-Weight Manipulator Applications Involving Compliant Interacting Environments and Compliant Bases." In ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/esda2014-20136.

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The paper defines impedance control based control laws for interaction tasks with environments of unknown geometrical and mechanical properties, both considering manipulators mounted on A) rigid and B) compliant bases. In A) a deformation-tracking strategy allows the control of a desired deformation of the target environment. In B) a force-tracking strategy allows the control of a desired interaction force. In both A) and B) the on-line estimation of the environment stiffness is required. Therefore, an Extended Kalman Filter is defined. In B) the on-line estimation of the robot base position is used as a feedback in the control loop. The compliant base is modelled as a second-order physical system with known parameters (offline identification) and the base position is estimated from the measure of interaction forces. The Extended Kalman Filter, the grounding position estimation and the defined control laws are validated in simulation and with experiments, especially dedicated to an insertion-assembly task with A) time-varing stiffness environment and B) constant stiffness environment.
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Li, Yijun, Taehyun Shim, Dexin Wang, and Timothy Offerle. "Comparative Study of Rack Force Estimation for Electric Power Assist Steering System." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5255.

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For an electric power assist steering (EPAS) control system, it is important to know the rack force information to improve the steering feel control performance. Since there is no direct measurement of rack force in current EPAS system, there have been various rack force estimation algorithms proposed for the control system development. In this paper, two existing rack force estimation methods (based on steering system dynamics and vehicle dynamics) have been implemented in the simulation environment to compare its performance. The effectiveness and limitations of two methods have been analyzed using a simulation of high fidelity EPAS model with various inputs conditions. In addition, new adaptation algorithm is proposed to further improve the estimation performance of the existing methods.
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Ali, Hussein F. M., Se-Woong Oh, and Youngshik Kim. "State Estimation of a Robotic Vehicle With Six In-Wheel Drives Using Kalman Filter." In ASME 2020 29th Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/isps2020-1937.

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Abstract This paper describes an estimation algorithm for a robotic vehicle with articulated suspension (RVAS) to estimate the vehicle velocity and acceleration states, and the tire forces. The RVAS is an unmanned ground vehicle based on a skid steering using an independent in-wheel motor at each wheel. The estimation algorithm consists of five parts. In the first part, a wheel state estimator estimates the wheel rotational speed and its angular acceleration using Kalman filter, which is used to estimate the longitudinal tire force distribution in the second part. The third part is to estimate respective longitudinal, lateral, and vertical speeds of the vehicle and wheels. Based on these speeds, the slip ratio and slip angle are estimated in the fourth part. In the fifth part, the vertical tire force is then estimated. For a simulation test environment, the RVAS dynamic model is developed using Matlab and Simulink. The RVAS model consists of five main parts which include in-wheel motor model, wheel dynamic model, Fiala tire model, arm dynamic model, and the sprung mass dynamic model. The estimation algorithm is then validated using the vehicle test data and different test scenarios. It is found from simulation results that the proposed estimation algorithm can estimate the vehicle states, longitudinal tire forces, and vertical tire forces efficiently.
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Reports on the topic "ENVIRONMENT FORCE ESTIMATION"

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Banerjee, Onil, Juan M. Murguia, Martin Cicowiez, and Adela Moreda. The Integrated Economic-Environmental Modeling (IEEM) Platform Approach to Tourism Investment Analysis: An Application to Costa Rica. Inter-American Development Bank, March 2020. http://dx.doi.org/10.18235/0002288.

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Public investment in different types of tourism, from business to leisure tourism, has differentiated impacts on local economies, environment, people and government revenues. A fully integrated analytical approach such as the Integrated Economic-Environmental Modeling (IEEM) Platform is required to capture these multi-dimensional impacts. Applying IEEM to public investment in tourism in Costa Rica we find: investing in a higher skilled labor force particularly in traditional tourism-related activities will improve household welfare; similar increases in demand across all types of tourism show that Health tourism generates the greatest impact on household welfare, while Business tourism has the best prospects for reducing unemployment; Business tourism generates the largest increase in government revenues, but also has the largest greenhouse gas emission footprint, and; the whole of economy perspective of IEEM that captures direct, indirect and induced impacts results in a higher Net Present Value estimation of the investment.
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Ayoul-Guilmard, Q., F. Nobile, S. Ganesh, M. Nuñez, R. Tosi, C. Soriano, and R. Rosi. D5.5 Report on the application of multi-level Monte Carlo to wind engineering. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.03.

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We study the use of multi-level Monte Carlo methods for wind engineering. This report brings together methodological research on uncertainty quantification and work on target applications of the ExaQUte project in wind and civil engineering. First, a multi-level Monte Carlo for the estimation of the conditional value at risk and an adaptive algorithm are presented. Their reliability and performance are shown on the time-average of a non-linear oscillator and on the lift coefficient of an airfoil, with both preset and adaptively refined meshes. Then, we propose an adaptive multi-fidelity Monte Carlo algorithm for turbulent fluid flows where multilevel Monte Carlo methods were found to be inefficient. Its efficiency is studied and demonstrated on the benchmark problem of quantifying the uncertainty on the drag force of a tall building under random turbulent wind conditions. All numerical experiments showcase the open-source software stack of the ExaQUte project for large-scale computing in a distributed environment.
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Meidani, Hadi, and Amir Kazemi. Data-Driven Computational Fluid Dynamics Model for Predicting Drag Forces on Truck Platoons. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-036.

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Fuel-consumption reduction in the truck industry is significantly beneficial to both energy economy and the environment. Although estimation of drag forces is required to quantify fuel consumption of trucks, computational fluid dynamics (CFD) to meet this need is expensive. Data-driven surrogate models are developed to mitigate this concern and are promising for capturing the dynamics of large systems such as truck platoons. In this work, we aim to develop a surrogate-based fluid dynamics model that can be used to optimize the configuration of trucks in a robust way, considering various uncertainties such as random truck geometries, variable truck speed, random wind direction, and wind magnitude. Once trained, such a surrogate-based model can be readily employed for platoon-routing problems or the study of pavement performance.
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