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Design, Modeling, and Control of a Low-Cost and Rapid Response Soft-Growing Manipulator for Orchard Operations

Authors :
Dorosh, Ryan
Allen, Justin
He, Zixuan
Ninatanta, Christopher
Coleman, Jack
Spieker, Jack
Tuck, Ethan
Kurtz, Jordan
Zhang, Qin
Whiting, Matthew D.
Luo, Jiecai
Karkee, Manoj
Luo, Ming
Publication Year :
2023

Abstract

Tree fruit growers around the world are facing labor shortages for critical operations, including harvest and pruning. There is a great interest in developing robotic solutions for these labor-intensive tasks, but current efforts have been prohibitively costly, slow, or require a reconfiguration of the orchard in order to function. In this paper, we introduce an alternative approach to robotics using a novel and low-cost soft-growing robotic platform. Our platform features the ability to extend up to 1.2 m linearly at a maximum speed of 0.27 m/s. The soft-growing robotic arm can operate with a terminal payload of up to 1.4 kg (4.4 N), more than sufficient for carrying an apple. This platform decouples linear and steering motions to simplify path planning and the controller design for targeting. We anticipate our platform being relatively simple to maintain compared to rigid robotic arms. Herein we also describe and experimentally verify the platform's kinematic model, including the prediction of the relationship between the steering angle and the angular positions of the three steering motors. Information from the model enables the position controller to guide the end effector to the targeted positions faster and with higher stability than without this information. Overall, our research show promise for using soft-growing robotic platforms in orchard operations.<br />Comment: International Conference on Intelligent Robots and Systems (IROS) 2023

Subjects

Subjects :
Computer Science - Robotics

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2311.00197
Document Type :
Working Paper