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THE 13TH SCIENTIFIC DAY (Catalyzing Innovation : Human Capital, Research, and Industry Linkages)
Published: August 23,2024Earth Resources and Geo-Environment Technology
Published: August 20,2024Word Spotting on Khmer Palm Leaf Manuscript Documents
Published: June 30,2024Text Image Reconstruction and Reparation for Khmer Historical Document
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Published: June 30,2024Walkability and Importance Assessment of Pedestrian Facilities in Phnom Penh City
Published: June 30,2024Assessment of Proximate Chemical Composition of Cambodian Rice Varieties
Published: June 30,2024Integration of RRT* Path Planning with Trajectory Tracking for Wheeled Mobile Robot
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1. Department of Industrial and Mechanical Engineering, Institute of Technology of Cambodia, Russian Federation Blvd., P.O. Box 86, Phnom Penh, Cambodia
Received: August 11,2022 / Revised: Accepted: October 18,2022 / Published: December 31,2022
Mobile robots have been around since the late 1960s. This kind of technology has caught the attention of many researchers since then. In the last decade, the applications of mobile robots are being applied in various sectors unleashing more benefits of automation and robotics to be captured to their maximum potential by mankind. As the tasks are getting more complex, it requires the mobile robots to be more advanced and autonomous. That is when motion planning comes into play. There are many types of wheeled mobile robots, one of which is called differential-drive. Although this type of robot has the benefits of simplicity over other types, it also has one downside, as it involves non-holonomic constraints. The problem of non-holonomic wheeled mobile robots in terms of path planning and tracking control are the big challenges for autonomous robot researchers throughout these years. Many approaches have been proposed and confirmed to have their own advantages and disadvantages in certain circumstances. This paper presents an integrated path planning and trajectory tracking control method for wheeled mobile robots allowing the robots to find the lowest-cost path while avoiding obstacles within a short computational time and move towards their goal by combining the RRT* path planning with Backstepping control. The performance of this integrated model is validated and implemented onto a two-wheel mobile robot which is a non-holonomic system subject to known static environmental obstacles. Assumptions and details on the test result are also described.