Locomotion Algorithm for Onroad Autonomous Robots with Real Time Response

Abstract

Abstract: This research introduces a novel locomotionalgorithm for autonomous on-road robots that are intended to realtime garbage collection from dustbins.The proposed system incorporates a cutting-edge object identification framework called YOLO (You Only Look Once) to recognise roadways, obstructions, and dustbins. The autonomous robot, equipped with a robust hardware platform and a camera, navigates urban environments efficiently, ensuring seamless obstacle avoidance and precise dustbin localization.Our method makes use of real-time processing to facilitate adaptive decision-making and dynamic path planning, which improves the robot's operational effectiveness. The algorithm's efficacy in varioussettings is illustrated by the experimental findings, underscoring its potential for scalable implementation in smart city endeavours. Recent advances in autonomous urban cleaning systems form the basis for this study, which focuses on real-time processing capabilities to enable adaptive decisionmaking and smooth navigation. Experimental validation illustratesthe suggested locomotion algorithm's performance in avariety of urban environments, highlighting its practical application in autonomous garbage management systems. This research aims to address waste management difficulties and contribute to the development of autonomous urban cleaning technology, thereby supporting the realisation of smarter and cleaner cities. By providing a long-term solution to the problems associated with urban waste management, this research advances autonomous urban cleaning systems.