Rapid Short-Time Path Planning for Phase Space

2011 ◽  
Vol 23 (2) ◽  
pp. 271-280 ◽  
Author(s):  
Chyon Hae Kim ◽  
◽  
Hiroshi Tsujino ◽  
Shigeki Sugano ◽  
Keyword(s):  
Phase Space ◽  
Path Planning ◽  
Dynamic Models ◽  
Optimal Motion ◽  
Time Path ◽  
Planning Algorithm ◽  
General Phase ◽  
Pruning Algorithms ◽  
Short Time ◽  
Path Planning Algorithm

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.

Life Extending Minimum-Time Path Planning for a Hexapod Robot

2010 ◽  
Author(s):  
Xin Wu ◽  
Yaoyu Li ◽  
Thomas R. Consi
Keyword(s):  
Fatigue Life ◽  
Path Planning ◽  
Radial Force ◽  
Minimum Time ◽  
Life Extension ◽  
Euler Formula ◽  
Time Path ◽  
Degradation Rates ◽  
Planning Algorithm ◽  
Path Planning Algorithm

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.

A Real-Time Path-Planning Algorithm based on Receding Horizon Techniques

2017 ◽  
Vol 91 (3-4) ◽  
pp. 445-457 ◽  
Author(s):  
M. Murillo ◽  
G. Sánchez ◽  
L. Genzelis ◽  
L. Giovanini
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Receding Horizon ◽  
Time Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm

scholarly journals A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zeyuan Liu ◽  
Cuntao Liu ◽  
Wendong Zhao ◽  
Aijing Li
Keyword(s):  
Path Planning ◽  
User Satisfaction ◽  
Information Acquisition ◽  
Planning Problem ◽  
Total Satisfaction ◽  
Planning Algorithm ◽  
Data Ferry ◽  
Short Time ◽  
Path Planning Algorithm ◽  
User Priority

This paper considers a reconnaissance scenario where multiple unmanned aerial vehicles (UAVs) provide services cooperatively for multiple users with different priorities. Although users all expect to acquire their needed information in a short time, the degree of urgency to meet their demands is different when taking their diverse priorities into account. A priority-driven multiuser satisfaction model is designed, where users’ satisfaction is quantified based on their different priorities, information acquisition demands, and the time they obtain their desired information. To ensure high priority users’ fast information acquisition while avoiding excessive delay in low priority users’ information acquisition, a batchwise information backhaul strategy is adopted. In each batch, a UAV is selected as the data ferry through a consultative mechanism to carry information back to users. This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. The simulation results show that compared with traditional path planning algorithms without considering user satisfaction, our proposed algorithm can guarantee faster information acquisition for users with higher priorities, which leads to higher satisfaction. In addition, the applicability of our proposed reconnaissance strategy and path planning algorithm in different situations is also analyzed.

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