Path Avoidance System of Intelligent Robot Based on Computer Vision

Abstract

At present, obstacle avoidance technology is widely used in the military field, scientific detection, traffic control, industrial manufacturing, medical service, and many other fields, and various machines with autonomous navigation and obstacle avoidance capabilities have been used to varying degrees, thus replacing some human daily production activities and bringing many conveniences to people’s lives. The key to autonomous obstacle avoidance is to obtain the direction information of the obstacle in its direction of advance in real time, which is also the precondition of obstacle avoidance system in obstacle avoidance path planning. In this paper, an intelligent robot path avoidance system is designed based on computer vision (CV) theory. The binocular vision ranging experiment verifies that the system has a less ranging error and can effectively detect the location of obstacles within a certain range, and the success rate of intelligent robot avoidance of obstacles reaches more than 96%, achieving a good avoidance effect.

Advancements in Learning-Based Navigation Systems for Robotic Applications in MRO Hangar: Review

“…Poor sensor data can affect the stability, reliability, and performance of robotic solutions. They can be subject to high levels of inaccuracies and noise in sensor data that breed uncertainties and deviations in performance, which affects safe navigation [ 117 ]. Calibrating and simulating sensors to match real sensor specifications are essential to bridge the gap.…”