Intelligent Soft Robot Mobility in the Real World

The goal of this project is the creation of soft, snake-like robots that can navigate through real environments with confined spaces, fragile objects, clutter, rough and/or granular surfaces. This project is lead by Prof. Cagdas Onal (PI) from WPI Soft Robotics Lab  and Prof. Jie Fu (Co-PI) from Control and Intelligent Robotics Lab (CIRL). Specifically, we plan to develop adaptive and robust control for the soft snake robotics given the difficulty-to-model dynamics. We will investigate learning-based control and stochastic planning to enable the snake robot effectively interacting with obstacles, and autonomously navigating under uneven and open environments under high-level, complex task specifications. When successful, we expect to deploy such a system for geo-exploration and search-and-rescue.

The theory and methods developed with this project could provide new methods to control soft robotics, with applications to safe human-robot interaction.

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Team Members: 

Renato Gasoto, Yinan Sun, Xuan Liu.

Sponsor: National Science Foundation

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Related publications:

  • Renato Gasoto, Miles Macklin, Xuan Liu, Yinan Sun, Kenny Erleben, Cagdas Onal, Jie Fu, “A Validated Physical Model For Real-Time Simulation of Soft Robotic Snakes”, Accepted by IEEE International Conference on Robotics and Automation (ICRA), 2019.
  • Renato Gasoto, Jie Fu, “Efficient Reinforcement Learning With Parametric State Clustering”, submitted, 2018.
  • Erik Skorina, Ming Luo, Weijia Tao, Fuchen Chen, Jie Fu, Cagdas Onal, “Adapting to Flexibility: Model Reference Adaptive Control of Soft Bending Actuators”, IEEE Robotics and Automation Letters, 2017, accepted.

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