Life Extending Minimum-Time Path Planning for a Hexapod Robot

Author(s):  
Xin Wu ◽  
Yaoyu Li ◽  
Thomas R. Consi

This paper presents a life extending minimum-time path planning algorithm for legged robots, with application for a six-legged walking robot (hexapod). The leg joint fatigue life can be extended by reducing the constraint on the dynamic radial force. The dynamic model of the hexapod is built with the Newton Euler Formula. In the normal condition, the minimum-time path planning algorithm is developed through the bisecting-plane (BP) algorithm with the constraints of maximum joint angular velocity and acceleration. According to the fatigue life model for ball bearing, its fatigue life increases while the dynamic radial force on the bearing decreases. The minimum-time path planning algorithm is thus revised by reinforcing the constraint of maximum radial force based on the expectation of life extension. A symmetric hexapod with 18 degree-of-freedom is used for simulation study. As a simplified treatment, the magnitudes of dynamic radial force on proximal joints at the pair of supporting legs are set identical to achieve similar degradation rates on each joint bearing and obtain the dynamic radial force on each joint. The simulation results validate the effectiveness of the proposed idea. This scheme can extend the operating life of robot (joint bearing fatigue life) by modifying the joint path only without affecting the primary task specifications.

2011 ◽  
Vol 23 (2) ◽  
pp. 271-280 ◽  
Author(s):  
Chyon Hae Kim ◽  
◽  
Hiroshi Tsujino ◽  
Shigeki Sugano ◽  

This paper addresses optimal motion for general machines. Approximation for optimal motion requires a global path planning algorithm that precisely calculates the whole dynamics of a machine in a brief calculation. We propose a path planning algorithm that consists of path searching and pruning algorithms. The pruning algorithmis based on our analysis of state resemblance in general phase space. To confirm precision, calculation cost, optimality and applicability of the proposed algorithm, we conducted several shortest time path planning experiments for the dynamic models of double inverted pendulums. Precision to reach the goal states of the pendulums was better than other algorithms. Calculation cost was 58 times faster at least. We could tune optimality of proposed algorithm via resolution parameters. A positive correlation between optimality and resolutions was confirmed. Applicability was confirmed in a torque based position and velocity feedback control simulation. As a result of this simulation, the double inverted pendulums tracked planned motion under noise while keeping within torque limitations.


2017 ◽  
Vol 91 (3-4) ◽  
pp. 445-457 ◽  
Author(s):  
M. Murillo ◽  
G. Sánchez ◽  
L. Genzelis ◽  
L. Giovanini

Sign in / Sign up

Export Citation Format

Share Document