Guidelines in nonholonomic motion planning for mobile robots

Author(s):  
J. P. Laumond ◽  
S. Sekhavat ◽  
F. Lamiraux
Robotics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 96
Author(s):  
Yankai Wang ◽  
Qiaoling Du ◽  
Tianhe Zhang ◽  
Chengze Xue

Hybrid mobile robots with two motion modes of a wheeled vehicle and truss structure with the ability to climb poles have significant flexibility. The motion planning of this kind of robot on a pole has been widely studied, but few studies have focused on the transition of the robot from the ground to the pole. In this study, a locomotion strategy of wheeled-legged pole-climbing robots (the WL_PCR) is proposed to solve the problem of ground-to-pole transition. By analyzing the force of static and dynamic process in the ground-to-pole transition, the condition of torque provided by the gripper and moving joint is proposed. The mathematical expression of Centre of Mass (CoM) of the wheeled-legged pole-climbing robots is utilized, and the conditions for the robot to smoothly transition from the ground to the vertical pole are proposed. Finally, the feasibility of this method is proved by the simulation and experimentation of a locomotion strategy on wheeled-legged pole-climbing robots.


Author(s):  
Xin-Sheng Ge ◽  
Li-Qun Chen

The motion planning problem of a nonholonomic multibody system is investigated. Nonholonomicity arises in many mechanical systems subject to nonintegrable velocity constraints or nonintegrable conservation laws. When the total angular momentum is zero, the control problem of system can be converted to the motion planning problem for a driftless control system. In this paper, we propose an optimal control approach for nonholonomic motion planning. The genetic algorithm is used to optimize the performance of motion planning to connect the initial and final configurations and to generate a feasible trajectory for a nonholonomic system. The feasible trajectory and its control inputs are searched through a genetic algorithm. The effectiveness of the genetic algorithm is demonstrated by numerical simulation.


Robotics ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 20 ◽  
Author(s):  
A poorva ◽  
Rahul Gautam ◽  
Rahul Kala

2002 ◽  
Vol 68 (665) ◽  
pp. 165-172
Author(s):  
Atsushi YAMASHITA ◽  
Masaki FUKUCHI ◽  
Jun OTA ◽  
Tamio ARAI ◽  
Hajime ASAMA

2021 ◽  
Author(s):  
Xuehao Sun ◽  
Shuchao Deng ◽  
Baohong Tong ◽  
Shuang Wang ◽  
Shuai Ma ◽  
...  

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