Using a hyper-ellipsoid clustering Kohonen for autonomous mobile robot map building, place recognition and motion planning

2002 ◽  
Author(s):  
J.A. Janet ◽  
S.M. Scoggins ◽  
M.W. White ◽  
J.C. Sutton ◽  
E. Grant ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Place Recognition ◽  
Map Building ◽  
Autonomous Mobile Robot

A New Cockroach Swarm Optimization for Motion Planning of Mobile Robot

2012 ◽  
Vol 263-266 ◽  
pp. 834-838
Author(s):  
Wanhui Liu ◽  
Le Cheng
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Euclidean Distance ◽  
Optimal Path ◽  
Autonomous Mobile Robot ◽  
Weight Factor ◽  
Simulation Experiments ◽  
Swarm Optimization ◽  
Heuristic Information

In this paper, an improved cockroach swarm optimization, called cockroach swarm optimization with expansion gird (CSO-EG), is presented and applied to motion planning of autonomous mobile robot. In CSO-EG, the expansion gird method is used to model workspace. By computing the weight factor, the Euclidean distance from each candidate to the destination cell and the pheromone strength of each candidate cell are use as the heuristic information together. For increasing the variety of path, a random choosing cell strategy is introduced. The simulation experiments demonstrate that the CSO-EG algorithm can quickly get the optimal or near-optimal path in a workspace populated with obstacles.

AN INTEGERATED NAVIGATION SYSTEM FOR AUTONOMOUS MOBILE ROBOT IN DYNAMIC ENVIROMENTS

2020 ◽  
pp. 32-46
Author(s):  
Nguyen Lan Anh
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Navigation System ◽  
Tracking System ◽  
Dynamic Environment ◽  
Planning System ◽  
Autonomous Mobile Robot ◽  
Integrated Navigation ◽  
Elastic Band ◽  
Integrated Navigation System

To enable an autonomous mobile robot to navigate safely in a dy- namic environment, the mobile robot must address four typical functional blocks of the navigation system including perception, localization, motion planning, and motor control. In this study, we present an integrated navigation system for the autonomous mobile robot in the dynamic environment by incorporating the techniques proposed in our previous studies, including object detection and tracking system, localization system and motion planning system, into a completed navigation system. In addition, we propose an extended timed elastic band (ETEB) technique for online trajectory planning, which allows the mobile robot to proactively avoid obstacles in the surrounding environment. We validate the effectiveness of the proposed model through a series of experiments in both simulated and real-world environments. The experimental results show that our proposed motion model is capable of driving the mobile robots to proactively avoid dynamic obstacles, providing safe navigation for the robots.

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