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Researchers at West Virginia University presented a force-aware branch manipulation framework for agricultural robots at IROS 2025. The system uses an RRT*-based motion planner that models branches as deformable linear objects, combined with real-time force feedback to safely move plant branches and expose hidden flowers or fruits. When measured interaction forces exceed a safe threshold, the robot replans online to find alternative paths. Tested across 50 trials, the approach achieved a 78% success rate and reduced manipulation forces from over 100 N to below 40 N. The work is motivated by StickBug, a six-armed precision pollination robot, and aims to enable multi-arm systems where one arm manipulates branches while another performs pollination, pruning, or harvesting.

A multi-armed robot for assisting with agricultural tasks