Lakhal, Othman (University of Lille, CRIStAL, CNRS-UMR 9189,), belarouci, abdelkader (CRIStAL-UNiversity of Lille), chettibi, taha (école militaire polytechnique), Merzouki, Rochdi (Ecole Polytechnique de Lille)

Inverse Kinematics-Based Redundancy Resolution for Automated Mushroom Harvesting

Scheduled for presentation during the Regular Session "Optimisation" (WeCD), Wednesday, June 11, 2025, 17:50−18:10,

33rd Mediterranean Conference on Control and Automation, June 10-13, 2025, Tangier, Morocco

This information is tentative and subject to change. Compiled on May 9, 2025

Abstract

Automated mushroom harvesting is challenging, especially in vertically stacked growing environments, due to limited space, the delicate nature of the crop, and the need for precise robot motion. This paper presents CeuiBot, a robotic system composed of two SCARA-type manipulators, each mounted on a linear rail, and installed on a mobile base that moves between shelves. The system is designed to operate efficiently in constrained agricultural environments. Unlike traditional approaches that focus on avoiding joint limits or minimizing torque, our contribution is at the control level. We propose an optimization strategy that reduces redundant motion by minimizing prismatic rail displacement and limiting the simultaneous activation of multiple joints. Our method is based on a workspace-aware inverse kinematics formulation that prioritizes minimal rail movement while maintaining target reachability. A workspace segmentation technique is also introduced to avoid singularities and self-collisions. Experimental results show a significant improvement in trajectory efficiency, reduced actuator usage, and optimized energy consumption. The proposed approach is efficient, robust, and compatible with real-time computation, making it suitable for selective mushroom harvesting in confined farming environments.