Accelerating Bi-Directional Sampling-Based Search for Motion Planning of Non-Holonomic Mobile Manipulators
| Autor: | Pradeep Rajendran, Ariyan M. Kabir, Shantanu Thakar, Hyojeong Kim, Satyandra K. Gupta |
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| Rok vydání: | 2020 |
| Předmět: |
Nonholonomic system
0209 industrial biotechnology Mathematical optimization Robot kinematics Computer science Heuristic (computer science) Holonomic Sampling (statistics) 02 engineering and technology Acceleration Tree (data structure) 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Motion planning Manipulator |
| Zdroj: | IROS |
| Popis: | Determining a feasible path for nonholonomic mobile manipulators operating in congested environments is challenging. Sampling-based methods, especially bi-directional tree search-based approaches, are amongst the most promising candidates for quickly finding feasible paths. However, sampling uniformly when using these methods may result in high computation time. This paper introduces two techniques to accelerate the motion planning of such robots. The first one is coordinated focusing of samples for the manipulator and the mobile base based on the information from robot surroundings. The second one is a heuristic for making connections between the two search trees, which is challenging owing to the nonholonomic constraints on the mobile base. Incorporating these two techniques into the bi-directional RRT framework results in about 5x faster and 10x more successful computation of paths as compared to the baseline method. |
| Databáze: | OpenAIRE |
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