Regular perturbations to the motion of a three-wheeled mobile robot with the front-wheel drive under restricted state variables*

Author(s):  
Roman Chertovskih ◽  
Anna Daryina ◽  
Askhat Diveev ◽  
Dmitry Karamzin ◽  
Fernando L. Pereira ◽  
...  
1996 ◽  
Vol 8 (1) ◽  
pp. 93-103
Author(s):  
Masafumi Hashimoto ◽  
◽  
Fuminori Oba ◽  
Yasushi Fujikawa ◽  
Kazutoshi Imamaki ◽  
...  

This paper describes a position estimation method for a wheeled mobile robot by integrating information in an odometric dead reckoning and a laser navigation system. Dead reckoning regularly gives the robot positions by the rotational counts of the two side wheels. The laser navigation system successively observes the bearing angles relative to the corner cube reflectors fixed in the robot environment. The chi-squared hypothesis testing is applied to reliably identify the corner cubes. The identified angle measurements modify the robot positions calculated by the dead reckoning based on the Extended Kalman filtering. A plant model is introduced from the kinematic equation concerning the dead reckoning, which-regards both the robot position and the wheel’s radius as state variables and the encoder measurement as an input variable. A measurement model is built concerning the bearing to a corner cube reflector in the environment observed by the scanned laser. The proposed method enables the robot to accurately estimate its position even under uncertainty of the wheel’s radius and the robot motion with slippage in a cluttered environment. The simulation and experimental results justify the proposed method.


Author(s):  
An-Ding Zhu ◽  
Guan-Nan He ◽  
Shun-Chang Duan ◽  
Wei-Han Li ◽  
Xian-Xu Bai

Abstract This article formulates a front-wheel-drive three-degree-of-freedom (3DOF) four-wheel planar vehicle model with the Magic Formula tire model. The state variables' evolutions of the model, i.e., trajectories of the model under acceleration and deacceleration conditions, are analyzed. The process of evolution is divided into desirable and undesirable phases based on the response characteristics of the vehicle to the driver input during the process. The trajectories are categorized as unsaturated trajectories and saturated trajectories by the existence of saturated tires during these phases. The response of state variables to driver input under acceleration conditions during undesirable phases are zero or even opposite, while the response of undesirable phases under the deacceleration condition is partially positive. Besides, the existing yaw rate safety envelope is recalibrated by using a longitudinal and lateral tire force coupling model. A more accurate yaw rate safety envelope is obtained from the given driver input. Furthermore, a longitudinal speed safety envelope is proposed according to the relationships among slip angle, yaw rate, and longitudinal speed. These safety envelopes are determined by driver input, tire properties, and grip condition. After overlaying yaw rate and longitudinal speed safety envelopes in the state space, the feasibility of using the safety envelope as trajectory classification criteria is discussed.


Robotica ◽  
2014 ◽  
Vol 33 (7) ◽  
pp. 1393-1414 ◽  
Author(s):  
Chong Yu ◽  
Xiong Chen

SUMMARYIn this paper, an iterative learning control algorithm is adopted to solve the high-precision trajectory tracking issue of a wheeled mobile robot with time-varying, nonlinear, and strong-coupling dynamics properties. The designed iterative learning control law adopts predictive, current and past learning items to drive the state variables, and input variables, and outputs variables converge to the bounded scope of their desired values. The algorithm can enhance the control performance, stability and robust characteristics. The rigorous mathematical proof of the convergence character of the proposed iterative learning control algorithm is given. The feasibility, effectiveness, and robustness of the proposed algorithm are illustrated by quantitative experiments and comparative analysis. The experimental results show that the proposed iterative learning control algorithm has an outstanding control effect on the trajectory tracking issue of wheeled mobile robots.


2016 ◽  
Vol 9 (3) ◽  
pp. 215-221
Author(s):  
Junpeng Shao ◽  
Tianhua He ◽  
Jingang Jiang ◽  
Yongde Zhang

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