Open AccessNAVIGATION OF MOBILE ROBOT- ALGORITHM FOR PATH PLANNING & COLLISION AVOIDANCE- A REVIEW
Author(s) -
V. Keerthana,
C. Kiruthiga,
P. Kiruthika,
V. Sowmiya,
R. Manikadan
Publication year - 2017
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v5.i1.2017.1735
Subject(s) - mobile robot , obstacle avoidance , collision avoidance , obstacle , robot , motion planning , mobile robot navigation , path (computing) , collision , computer science , artificial intelligence , robot control , robotics , real time computing , simulation , computer network , geography , computer security , archaeology
The eld of autonomous mobile robotics has recently gained many researchers’ interests. Due to the specic needs required by various applications of mobile robot systems, especially in navigation, designing a real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective of our project is applications based mobile robot systems, especially in navigation, designing real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective behind using the obstacle avoidance approach is to obtain a collision-free trajectory from the starting point to the target in monitoring environments. The ability of the robot to follow a path, detects obstacles, and navigates around them to avoid collision. It also shows that the robot has been successfully following very congested curves and has avoided any obstacle that emerged on its path. Motion planning that allows the robot to reach its target without colliding with any obstacles that may exist in its path.
To avoid collision in the mobile robot environment, providing a path planning& line following approach. Line following, path planning, collision avoidance, back propagation, improved memory, detecting long distance obstacles. Cheap and economical than the former one. Also work with back propagation technique.