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A Berry Picking Robot With A Hybrid Soft-Rigid Arm: Design and Task Space Control

We present a hybrid rigid-soft arm and manipulator for performing tasks requiring dexterity and reach in cluttered environments. Our system combines the benefit of the dexterity of a variable length soft manipulator and the rigid support capability of a hard arm. The hard arm positions the extendable soft manipulator close to the target, and the soft arm manipulator navigates the last few centimeters to reach and grab the target. A novel magnetic sensor and reinforcement learning based control is developed for end effector position control of the robot. A compliant gripper with an IR reflectance sensing system is designed, and a k-nearest neighbor classifier is used to detect target engagement. The system is evaluated in several challenging berry picking scenarios.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Reinforcement Learning and Robotics
🐣 Hot Topic Early Bird - k-nearest neighbor

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