Dynamic and Static Obstacles Avoidance Strategies using Parallel Elliptic Limit-Cycle Approach for Autonomous Robots

In the context of intelligent robotic vehicles, obstacle avoidance has become the most challenging task in the development of Advanced Driving Assistance System (ADAS) for autonomous robots. In this paper, we discuss the path planning method for dynamic obstacle avoidance based on the Parallel Elliptic Limit Cycle approach, which has been shown to be effective in a static environment. In this paper, one approach for avoiding obstacles is to use the Parallel Elliptic Limit-Cycle (PELC) method, which is a control strategy that generates limit cycles in the state space of the robot. The PELC can be used for static and dynamic obstacle avoidance. A Feedback Linearization control is used for trajectory planning. Simulation results demonstrate the effectiveness of the proposed method for obstacle avoidance for an autonomous robot in the presence of dynamic and static obstacles.