scholarly journals Self-Organizing Migrating Algorithm with narrowing search space strategy for robot path planning

2021 ◽  
pp. 108270
Author(s):  
Quoc Bao Diep ◽  
Thanh Cong Truong ◽  
Swagatam Das ◽  
Ivan Zelinka
2008 ◽  
Vol 31 ◽  
pp. 497-542 ◽  
Author(s):  
M. R.K. Ryan

Multi-robot path planning is difficult due to the combinatorial explosion of the search space with every new robot added. Complete search of the combined state-space soon becomes intractable. In this paper we present a novel form of abstraction that allows us to plan much more efficiently. The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly. Planning then becomes a search in the much smaller space of subgraph configurations. Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search. We prove that this technique is sound and complete and demonstrate its practical effectiveness on a real map. A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness. The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which outperforms either approach alone.


2010 ◽  
Vol E93-D (3) ◽  
pp. 569-582 ◽  
Author(s):  
Aram KAWEWONG ◽  
Yutaro HONDA ◽  
Manabu TSUBOYAMA ◽  
Osamu HASEGAWA

1989 ◽  
Author(s):  
Jerome Barraquand ◽  
Bruno Langlois ◽  
Jean-Claude Latombe

Author(s):  
Baoyu Shi ◽  
Hongtao Wu

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.


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