An Adaptive Unscented Kalman Filter-based Controller for Simultaneous Obstacle Avoidance and Tracking of Wheeled Mobile Robots with Unknown Slipping Parameters

Cui, Mingyue; Liu, Hongzhao; Liu, Wei; Qin, Yi

doi:10.1007/s10846-017-0761-9

Cited by 34 publications

(25 citation statements)

References 27 publications

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“…The continuous methods estimate the position of a robot with a single state and have been applied to mobile robot localization with substantial success in terms of accuracy and efficiency. The representative algorithms of the continuous approach include the Kalman filter , extended Kalman filter , and unscented Kalman filter . Because these methods maintain only a single state, they are mainly used to track the position of the robot after the global localization .…”

Section: Related Workmentioning

confidence: 99%

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

Lee

Myung

2019

ETRI Journal

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This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

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Section: Related Workmentioning

confidence: 99%

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

Lee

Myung

2019

ETRI Journal

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“…Roy et al in [ 22 ] proposed an adaptive switching gain-based robust control that considers linear parametric uncertainty, whose efficacy was experimentally assessed with an adaptive SMC. Cui et al in [ 23 ] reported a robust control algorithm for solving the tracking and obstacle avoidance tasks that uses an adaptive unscented Kalman filter for estimating the slippage of the wheels and an unscented Kalman filter for adjusting the covariance of the noise generated by the slippage estimation process. In [ 24 ], Dönmez et al designed a visual servoing go-to-goal behavior controller to steer the DDWMR to a static target; such a controller was also experimentally assessed with two controls, a PID control and a fuzzy-PID control.…”

Section: Introductionmentioning

confidence: 99%

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

García-Sánchez

Tavera-Mosqueda

Silva‐Ortigoza

et al. 2020

Sensors

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In order to solve the trajectory tracking task in a wheeled mobile robot (WMR), a dynamic three-level controller is presented in this paper. The controller considers the mechanical structure, actuators, and power stage subsystems. Such a controller is designed as follows: At the high level is a dynamic control for the WMR (differential drive type). At the medium level is a PI current control for the actuators (DC motors). Lastly, at the low level is a differential flatness-based control for the power stage (DC/DC Buck power converters). The feasibility, robustness, and performance in closed-loop of the proposed controller are validated on a DDWMR prototype through Matlab-Simulink, the real-time interface ControlDesk, and a DS1104 board. The obtained results are experimentally assessed with a hierarchical tracking controller, recently reported in literature, that was also designed on the basis of the mechanical structure, actuators, and power stage subsystems. Although both controllers are robust when parametric disturbances are taken into account, the dynamic three-level tracking controller presented in this paper is better than the hierarchical tracking controller reported in literature.

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“…There have been many different approaches taken to improve accuracy or robot positioning. One approach by M. Cui, H. Liu, W. Liu, and Y. Qin used an unscented Kalman filter to attempt to estimate slip parameters of a wheeled robot [3]. The filter was combined with a unified controller with promising results.…”

Section: Introductionmentioning

confidence: 99%

Development of a Control and Estimation Strategy for a Six-Link Robot Manipulator

Hall¹,

Lee²,

Gadsden³

2020

Progress in Canadian Mechanical Engineering. Volume 3

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This paper covers the ongoing approach of creating new combinations of robot controllers with filtering techniques. It outlines the need for such a system and a current controller system that uses filtering techniques to improve accuracy. It also explains how the proposed approach differs from the systems in literature. This paper outlines how the system is designed and tested. It explains the approach taken to design a system, and how the performance of the system will be measured. Finally, it explains progress that has been achieved, as well as recommendations for future work.

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An Adaptive Unscented Kalman Filter-based Controller for Simultaneous Obstacle Avoidance and Tracking of Wheeled Mobile Robots with Unknown Slipping Parameters

Cited by 34 publications

References 27 publications

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

A Novel Dynamic Three-Level Tracking Controller for Mobile Robots Considering Actuators and Power Stage Subsystems: Experimental Assessment

Development of a Control and Estimation Strategy for a Six-Link Robot Manipulator

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