Path Planning and Obstacle Avoidance for Autonomous Mobile Robots: A Review

2006 ◽  
pp. 537-544 ◽  
Author(s):  
Voemir Kunchev ◽  
Lakhmi Jain ◽  
Vladimir Ivancevic ◽  
Anthony Finn
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Autonomous Mobile Robots

State-chain sequential feedback reinforcement learning for path planning of autonomous mobile robots

2013 ◽  
Vol 14 (3) ◽  
pp. 167-178 ◽  
Author(s):  
Xin Ma ◽  
Ya Xu ◽  
Guo-qiang Sun ◽  
Li-xia Deng ◽  
Yi-bin Li
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Mobile Robots ◽  
Autonomous Mobile Robots

A Real-time Algorithm for Obstacle Avoidance of Autonomous Mobile Robots

Robotica ◽  
1992 ◽  
Vol 10 (3) ◽  
pp. 217-227 ◽  
Author(s):  
Huang Han-Pang ◽  
Lee Pei-Chien
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Time Algorithm ◽  
Autonomous Mobile Robots ◽  
Computational Time ◽  
Avoidance Problem

SUMMARYA real-time obstacle avoidance algorithm is proposed for autonomous mobile robots. The algorithm is sensor-based and consists of a H-mode and T-mode. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. It will be shown that the algorithm is more efficient and more robust than other sensor-based algorithms. In addition, the algorithm will guarantee a solution for the obstacle avoidance problem. Since the algorithm only takes up a small computational time, it can be implemented in real time.

scholarly journals An Inverse Pheromone Approach in a Chaotic Mobile Robot’s Path Planning Based on a Modified Logistic Map

Technologies ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 84
Author(s):  
Eleftherios K. Petavratzis ◽  
Christos K. Volos ◽  
Lazaros Moysis ◽  
Ioannis N. Stouboulos ◽  
Hector E. Nistazakis ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Efficient Method ◽  
Chaotic Motion ◽  
Logistic Map ◽  
Autonomous Mobile Robots ◽  
Motion Pattern ◽  
Major Topic ◽  
Random Bit Generator ◽  
Modified Logistic Map

One major topic in the research of path planning of autonomous mobile robots is the fast and efficient coverage of a given terrain. For this purpose, an efficient method for covering a given workspace is proposed, based on chaotic path planning. The method is based on a chaotic pseudo random bit generator that is generated using a modified logistic map, which is used to generate a chaotic motion pattern. This is then combined with an inverse pheromone approach in order to reduce the number of revisits in each cell. The simulated robot under study has the capability to move in four or eight directions. From extensive simulations performed in Matlab, it is derived that motion in eight directions gives superior results. Especially, with the inclusion of pheromone, the coverage percentage can significantly be increased, leading to better performance.

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