Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination | Zendy

Yong Ma | Zendy; Hongwei Wang | Zendy; Langxiong Gan | Zendy; Min Guo | Zendy; Liwen Huang | Zendy; Jing Zhang | Zendy

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Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination

Author(s) -

Yong Ma,

Hongwei Wang,

Langxiong Gan,

Min Guo,

Liwen Huang,

Jing Zhang

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/902587

Subject(s) - baseline (sea) , motion planning , obstacle avoidance , computer science , robot , conflict resolution , smoothness , mobile robot , mathematical optimization , path (computing) , task (project management) , kinematics , start point , boundary (topology) , process (computing) , obstacle , real time computing , artificial intelligence , mathematics , engineering , end point , geography , systems engineering , law , mathematical analysis , oceanography , operating system , classical mechanics , political science , programming language , physics , geology , archaeology

This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach

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