In this work, we address the problem of deploying a multi-robot system for row crop phenotyping. We propose a sampling-based navigation algorithm for the team of robots to estimate the underlying spatial distribution in a field. We use Gaussian Process Models to predict the distribution of a scalar function in a field, and choose Mutual Information as a metric for selecting the future samples. With a row crop structure, we present a collision-free assignment and scheduling algorithm for the robots to reach the goal positions which minimizes the total traveling distance. The effectiveness of the proposed algorithm is demonstrated through simulations.
- Dynamic Systems and Control Division
Navigation Strategies for a Multi-Robot Ground-Based Row Crop Phenotyping Platform
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Gao, T, Emadi, H, Saha, H, Zhang, J, Lofquist, A, Singh, A, Ganapathysubramanian, B, Sarkar, S, Singh, A, & Bhattacharya, S. "Navigation Strategies for a Multi-Robot Ground-Based Row Crop Phenotyping Platform." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 3: Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. Atlanta, Georgia, USA. September 30–October 3, 2018. V003T32A009. ASME. https://doi.org/10.1115/DSCC2018-9096
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