Presentation + Paper
7 June 2024 Multirobot navigation using improved RRT*-SMART with digital twin technology
Elijah Riser, Timothy Sellers, Tingjun Lei, Pradeep Chintam, Chaomin Luo
Author Affiliations +
Abstract
Digital twin technology can play a significant role in multiple robots’ navigation by providing a virtual representation of the physical environment, robots, and their interactions. This high detail simulation can allow efficient and accurate navigation in difficult sc enarios wh ile en abling co st eff ective rob ot sol utions. In thi s res earch a multi-robot navigation system is developed using a reinforcement learning augmented RRT*-Smart algorithm. This proposed framework attempts to introduce a more efficient solution for navigating a partially known, static environment, while making use of the strengths of a centralized multi-robot system. The RRT*-Smart algorithm will be used to generate paths inside of the digital twin simulation consisting of both pre-gathered environment data as well as the LiDAR data received from the robots during operation. The various parameters of the RRT*- Smart algorithm will be tuned for each situation by use of reinforcement learning to allow for more adaptability. The effectiveness of this system is tested by use of a real-life simulation, with robots navigating their paths by use of the Dynamic Window Approach. The LiDAR data received from each robot is used to both avoid obstacles during navigation, as well as update the digital-twin map used by the RRT*-SMART path planner.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Elijah Riser, Timothy Sellers, Tingjun Lei, Pradeep Chintam, and Chaomin Luo "Multirobot navigation using improved RRT*-SMART with digital twin technology", Proc. SPIE 13052, Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024, 130520H (7 June 2024); https://doi.org/10.1117/12.3013872
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KEYWORDS
Robots

Computer simulations

Mathematical optimization

LIDAR

Navigation systems

Data modeling

Particle swarm optimization

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