A new gap-based obstacle avoidance approach: follow the obstacle circle method

Hosein Houshyari,Volkan Sezer

doi:10.1017/s0263574721001624

Abstract

AbstractOne of the most challenging tasks for autonomous robots is avoiding unexpected obstacles during their path following operation. Follow the gap method (FGM) is one of the most popular obstacle avoidance algorithms that recursively guides the robot to the goal state by considering the angle to the goal point and the distance to the closest obstacles. It selects the largest gap around the robot, where the gap angle is calculated by the vector to the midpoint of the largest gap. In this paper, a novel obstacle avoidance procedure is developed and applied to a real fully autonomous wheelchair. This proposed algorithm improves the FGM’s travel safety and brings a new solution to the obstacle avoidance task. In the proposed algorithm, the largest gap is selected based on gap width. Moreover, the avoidance angle (similar to the gap center angle of FGM) is calculated considering the locus of the equidistant points from obstacles that create obstacle circles. Monte Carlo simulations are used to test the proposed algorithm, and according to the results, the new procedure guides the robot to safer trajectories compared with classical FGM. The real experimental test results are in parallel to the simulations and show the real-time performance of the proposed approach.

Highlights

Motion planning refers to the robots’ ability to travel from the initial point toward the target without collisions
Given a goal state and a map of the environment and assuming that the obstacles are static and not changing during the travel time, the global planning algorithms can calculate the admissible trajectory on the maps’ collision-free spaces; the trajectory would be admissible because the map used in these categories of path planning algorithms is static and not updated dynamically [1, 2]
Experimental results Both follow the obstacle circle method (FOCM) and Follow the gap method (FGM) are coded in Python as independent robot operating system (ROS) nodes

Summary

Introduction

Motion planning refers to the robots’ ability to travel from the initial point toward the target without collisions These algorithms are developed to find the admissible path starting from the initial state toward the final state, depending on whether the map is given or not, and the type of obstacles, whether they are stable and static or dynamic. The latest study aiming to improve the FGM is represented in follow the dynamic gap method, [34] wherein the algorithm develops a new gap selection strategy for FGM, resulting in safe trajectories by considering the gap borders’ velocity vectors and the future gap change. A novel procedure for improving the classical FGM is developed and applied to a fully autonomous wheelchair This proposed algorithm, entitled as “follow the obstacle circle method (FOCM),” brings a new solution to the obstacle avoidance task that improves FGM’s travel safety.

Follow the gap method

Calculation of the final heading angle for each gap

Simulation results

Experimental platform

Conclusion