Obstacle Avoidance Method for Highly Redundant Robotic Arms

Abstract

Obstacle avoidance is an important concept to be considered when a robotic system is installed in an environment. Obstacles within the working space of a robotic system can prevent the robot from performing the tasks assigned to it properly; hence, the designer of the robotic system must program the robot to follow an emergency strategy that enables it to avoid any contact with a probable obstacle anywhere anytime within the working space of the robot. For mobile robots this task is relatively easier to accomplish since this type of robots have the flexibility to change their routes and take alternatives that are free of obstacles. For fixed robotic arm manipulators the situation is much more complex. In this paper we are only concerned with obstacle avoidance techniques and present a real-time obstacle avoidance method for fixed robotic arms that combines the benefits of both global and local techniques in that it can be used for both static and dynamic environments with a reduced computational effort.

A Hybrid AI-Based Adaptive Path Planning for Intelligent Robot Arms

“…This method effectively combines the advantages of both global and local techniques. It revolves around the concept of configuring the robot arm to manipulate its joints based on a specific polynomial selection, thereby addressing the inverse kinematics problem [25]. Furthermore, scholars have explored improved Machine Learning-based methods for adaptive path planning.…”

A Novel Hybrid Path Planning Method Based on Q-Learning and Neural Network for Robot Arm

“…Firas S. Hameed et al presented a real-time path planning method to avoid collision with obstacles for a fixed robot arm that combines the benefits of both global and local techniques. This method is based on the idea of configuring the robot arm to adjust its joints on a selected polynomial to solve the inverse kinematics problem [10]. Tse-Ching Lai et al proposed a path planning method to avoid collision with obstacles, based on non-uniform rational B-splines and a smooth polynomial [11].…”