Energy Efficient Planning for Repetitive Heterogeneous Tasks in Precision Agriculture
Xie, Shuangyu Goldberg, Ken Song, Dezhen
Xie, Shuangyu
Goldberg, Ken
Song, Dezhen
Supervisor
Department
Robotics
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Robotic weed removal in precision agriculture introduces a repetitive heterogeneous task planning (RHTP) challenge for a mobile manipulator. RHTP has two unique characteristics: 1) an observe-first-and-manipulate-later (OFML) temporal constraint that forces a unique ordering of two different tasks for each target and 2) energy savings from efficient task collocation to minimize unnecessary movements. RHTP can be framed as a stochastic renewal process. According to the Renewal Reward Theorem, the expected energy usage per task cycle is the long-run average. Traditional task and motion planning focuses on feasibility rather than optimality due to the unknown object and obstacle position prior to execution. However, the known target/obstacle distribution in precision agriculture allows minimizing the expected energy usage. For each instance in this renewal process, we first compute task space partition, a novel data structure that computes all possibilities of task multiplexing and its probabilities with robot reachability. Then we propose a region-based setcoverage problem to formulate the RHTP as a mixed-integer nonlinear programming. We have implemented and solved RHTP using Branch-and-Bound solver. Compared to a baseline in simulations based on real field data, the results suggest a significant improvement in path length, number of robot stops, overall energy usage, and number of replans.
Citation
S. Xie, K. Goldberg and D. Song, "Energy Efficient Planning for Repetitive Heterogeneous Tasks in Precision Agriculture," 2025 IEEE International Conference on Robotics and Automation (ICRA), Atlanta, GA, USA, 2025, pp. 7139-7145, doi: 10.1109/ICRA55743.2025.11128083
Source
International Conference on Robotics and Automation (ICRA)
Conference
2025 IEEE International Conference on Robotics and Automation (ICRA)
Keywords
Precision Agriculture, Multiplexing, Computational Modeling, Energy Conservation, Programming, Manipulators, Data Structures, Energy Efficiency, Data Models, Planning
Subjects
Source
2025 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
IEEE