NAVIGATION OF MOBILE ROBOT- ALGORITHM FOR PATH PLANNING & COLLISION AVOIDANCE- A REVIEW

V. Keerthana; C. Kiruthiga; P. Kiruthika; V. Sowmiya; R. Manikadan

doi:10.29121/granthaalayah.v5.i1.2017.1735

Authors

V.Keerthana Student, A.V.C College of Engineering, Manampandal, TamilNadu, India
C.Kiruthiga Student, A.V.C College of Engineering, Manampandal, TamilNadu, India
P.Kiruthika Student, A.V.C College of Engineering, Manampandal, TamilNadu, India
V.Sowmiya Student, A.V.C College of Engineering, Manampandal, TamilNadu, India
R.Manikadan Assistant Professor, A.V.C College of Engineering, Manampandal, TamilNadu, India

DOI:

https://doi.org/10.29121/granthaalayah.v5.i1.2017.1735

Keywords:

Collision Avoidance, Path Planning, Robotics Control, Webots, Mobile Robot, E-Puck

Abstract [English]

The ﬁeld of autonomous mobile robotics has recently gained many researchers’ interests. Due to the speciﬁc 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.

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