Publication Type : Conference Paper
Publisher : 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy)
Source : 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), IEEE, Kollam, India (2017)
Url : https://ieeexplore.ieee.org/document/8397373
ISBN : 9781538640210
Keywords : Collision avoidance, differential drive robot, Fuzzy control, Fuzzy controller, Genetic algorithm, Genetic algorithms, intelligent Fuzzy Controller, intelligent robot, intelligent robots, mobile robot, Mobile robots, motion control, obstacle avoidance, path optimization, Path Planning, Robot sensing systems, robot vision, Sensors, Target tracking, Trajectory following, wheeled differential robot, Wheels
Campus : Amritapuri
School : School of Engineering
Department : Electrical and Electronics
Year : 2017
Abstract : This work presents the design and simulation of a class of mobile robot namely differential drive robot, for target and path planning along with obstacle avoidance. A two wheeled differential robot is considered for this purpose. The target tracking is achieved by Go-to-Goal approach. Here the obstacle avoidance and target tracking is done along with time and path optimization using intelligent Fuzzy Controller and Genetic algorithm. Both the Genetic Algorithm and Fuzzy Controller are compared to find the flexibility and accuracy of the motion control. Different case studies are done to find which intelligent methodology is more efficient when it comes to path planning, target tracking and obstacle avoidance.
Cite this Research Publication : N. P. Varma, A. Vivek, and Dr. V. Ravikumar Pandi, “Target tracking, path planning and obstacle avoidance by intelligent robot”, in 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), Kollam, India, 2017.