Dynamic Behaviour of a Mobile Robot Vehicle with a Two Caster and Two Driving Wheel Configuration

Gentile, Angelo; Messina, A.R.; Trentadue, A.

doi:10.1080/00423119608968959

Cited by 6 publications

(11 citation statements)

References 3 publications

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“…The sub-objectives are usually judged by a heuristic function. The heuristic function in this paper is as follows [16]:…”

Section: Rolling Window Path Planningmentioning

confidence: 99%

“…Behavior dynamics uses point attractor and point repulsor to build robot behavior, and the robot's heading angle and motion speed are used as behavior variables to describe robots moving in a plane [14], but in the application, the line speed is limited by the heading angular velocity control and causes a deadlock; in addition, because of the non additivity of the virtual forces, there are also pseudo attractor problems. The literature [15,16] uses the linear velocity control method to solve this problem, but it is required that the linear velocity ensures that the robot's heading angle is always near the heading angle of the attractor. At the same time, there is also a situation in which the path between windows in the rolling windows method is not smooth because of the different directions of the robot motion.…”

Section: Introductionmentioning

confidence: 99%

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Indoor robot path planning assisted by wireless network

Wang

Nie

Zhu

2019

J Wireless Com Network

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Indoor robot global path planning needs to complete the motion between the starting point and the target point according to robot position command transmitted by the wireless network. Behavior dynamics and rolling windows in global path planning methods have limitations in their applications because the path may not be optimal, there could be a pseudo attractor or blind search in an environment with a large state space, there could be an environment where offline learning is not applicable to real-time changes, or there could be a need to set the probability of selecting the robot action. To solve these problems, we propose a behavior dynamics and rolling windows approach to a path planning which is based on online reinforcement learning. It applies Q learning to optimize the behavior dynamics model parameters to improve the performance, behavior dynamics guides the learning process of Q learning and improves learning efficiency, and each round of intensive learning action selection knowledge is gradually corrected as the Q table is updated. The learning process is optimized. The simulation results show that this method has achieved remarkable improvement in path planning. And, in the actual experiment, the robot obtains the target location information by wireless network, and plans an optimized and smooth global path online.

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“…The sub-objectives are usually judged by a heuristic function. The heuristic function in this paper is as follows [16]:…”

Section: Rolling Window Path Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Indoor robot path planning assisted by wireless network

Wang

Nie

Zhu

2019

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…However, to simplify the identification and control process of these dynamic models, the caster wheels were almost always removed and their contribution to the wheelchair's dynamics was instead considered as an external perturbation. This may be an acceptable compromise for the design of a wheelchair controller; however, when the caster wheels are not aligned with the rear wheels, which is the case in the curvilinear propulsion, their contribution to the wheelchair's dynamics is known to be important (Gentile et al 1996;Ding et al 2004). Thus, the caster wheels should be included in the modelling design.…”

Section: Introductionmentioning

confidence: 97%

A new dynamic model of the wheelchair propulsion on straight and curvilinear level-ground paths

Chénier

Bigras

Aïssaoui

2014

Computer Methods in Biomechanics and Biomedical Engineering

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Independent-roller ergometers (IREs) are commonly used to simulate the behaviour of a wheelchair propelled in a straight line. They cannot, however, simulate curvilinear propulsion. To this effect, a motorised wheelchair ergometer could be used, provided that a dynamic model of the wheelchair-user system propelled on straight and curvilinear paths (WSC) is available. In this article, we present such a WSC model, its parameter identification procedure and its prediction error. Ten healthy subjects propelled an instrumented wheelchair through a controlled path. Both IRE and WSC models estimated the rear wheels' velocities based on the users' propulsive moments. On curvilinear paths, the outward wheel shows root mean square (RMS) errors of 13% in an IRE vs 8% in a WSC. The inward wheel shows RMS errors of 21% in an IRE vs 11% in a WSC. Differences between both models are highly significant (p < 0.001). A wheelchair ergometer based on this new WSC model will be more accurate than a roller ergometer when simulating wheelchair propulsion in tight environments, where many turns are necessary.

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“…With this research, we develop a detailed dynamics model of a differential drive mobile robot (DDMR) towing an off-axle trailer that accounts for the swivel movement of caster wheels. Despite of the amount of literature devoted to investigate the effect of the swivel movement of caster wheels in the motion of DDMRs [7]- [9], to the best our knowledge, none of these works have been focused on studying the dynamic effect on the DDMR of the swivel movement of off-axle trailers' caster wheels. To incorporate such an effect into our models, the kinematic relation of the caster wheels' swivel rate with the velocity of the DDMR is computed considering the pure rolling and non-slipping constraints of the system.…”

Section: Introductionmentioning

confidence: 99%

Dynamics Model of a Differential Drive Mobile Robot Towing an Off-axle Trailer

Amezquita-Semprun¹,

Rosario²,

Chen³

2018

IJMERR

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Indoor navigation technology has enabled the exploitation of mobile robots for transportation of goods/materials in industry facilities/warehouses. Nevertheless, the deployment of a number of mobile robots segregated to individual tasks may limit the advantages of such technology. The achievement of a solution where a mobile robot capability is enhanced by aggregating passive mechanisms (i.e. passive trailers) represents a more cost effective and versatile solution. Therefore, the analysis of safety and performance of such configuration is a step forward toward the full deployment of this kind of systems. With this work, we attempt to contribute to this field by studying of the effects of system uncertainties, disturbances and changing operating conditions on the behavior of such systems. Specifically, we model the dynamics of a mobile robot towing an off-axle trailer with two wheels configurations and then incorporate the movement of the caster wheels in the dynamics model. Such a model would enable the synthesis of robust control schemes to achieve a better tracking capability and consistent performance in real operating scenarios.

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Dynamic Behaviour of a Mobile Robot Vehicle with a Two Caster and Two Driving Wheel Configuration

Cited by 6 publications

References 3 publications

Indoor robot path planning assisted by wireless network

Indoor robot path planning assisted by wireless network

A new dynamic model of the wheelchair propulsion on straight and curvilinear level-ground paths

Dynamics Model of a Differential Drive Mobile Robot Towing an Off-axle Trailer

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