Soft Growing Manipulator
2024
Modeling and Experimental Verification of a Continuous Curvature-Based Soft Growing Manipulator
Soft robots show significant potential for use in search and rescue, human-robot interaction, and other emerging fields due to their ability to easily conform, deform, and interact with their environment. However, precise control of these soft robots is still being explored. In this letter, we investigate a potential solution to address the limitations of precise control for soft robots. We experimentally verify the accuracy of a general analytical formulation of a continuous kinematic model using a custom soft growing manipulator. Next, we provide an experimental verification of its inverse kinematic model. With this precise model, most soft continuum kinematic models, whether tendon-driven or with a payload, can be represented. Our robot fits the proposed generalized curvature function for n=2 , with an average error relative to the robot’s overall length of 5.01%, based on four robot lengths of 0.5 m, 0.8 m, 1.0 m, and 1.2 m. The inverse kinematic model was verified using three positions, resulting in errors of 2.91%, 7.91%, and 2.14%. We also showed that the shape can be recovered based on using the tip position in the inverse kinematic model. Our future work will involve verifying this model in 3D space and incorporating it into a model-based feedback loop controller to enhance position control accuracy.
More detail:
J. Allen, R. Dorosh, C. Ninatanta, A. Allen, L. Shui, K. Yoshida, J. Luo, and M. Luo. Modeling and Experimental Verification of a Continuous Curvature-based Soft Growing Manipulator, IEEE Robotics and Automation Letters (2024), doi: 10.1109/LRA.2024.3369473
2023
Design, Modeling, and Control of a Low-Cost and Rapid Response Soft-Growing Manipulator for Orchard Operations
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.
More detail:
Ryan, J. Allen, Z. He, C. Ninatanta, J. Coleman, J. Spieker, E. Tuck, J. Kurtz, Q. Zhang, M. Whiting, J. Luo, M. Karkee, and M. Luo. “Design, Modeling, and Control of a Low-Cost and Rapid Response Soft-Growing Manipulator for Orchard Operations,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023: DETROIT, MI.