Robust learning of tensegrity robot control for locomotion through form-finding

Robots with flexible spines based on tensegrity structures have potential advantages over traditional designs with rigid torsos. However, these robots can be difficult to control due to their high-dimensional nonlinear dynamics. To overcome these issues, this work presents two controllers for tensegrity spine robots, using model-predictive control (MPC), and demonstrates the first closed-loop control of such structures. The first of the two controllers is formulated using only state tracking with smoothing constraints. The second controller, newly introduced in this work, tracks both state and input reference trajectories without smoothing. The reference input trajectory is calculated using a rigid-body reformulation of the inverse kinematics of tensegrity structures, and introduces the first feasible solutions to the problem for certain tensegrity topologies. This second controller significantly reduces the number of parameters involved in designing the control system, making the task much easier. The controllers are simulated with 2D and 3D models of a particular tensegrity spine, designed for use as the backbone of a quadruped robot. These simulations illustrate the different benefits of the higher performance of the smoothing controller versus the lower tuning complexity of the more general input-tracking formulation. Both controllers show noise insensitivity and low tracking error, and can be used for different control goals. The reference input tracking controller is also simulated against an additional model of a similar robot, thereby demonstrating its generality.

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“…Finally, since states {ξ (3) , ξ (15) , ξ (27) } are the vertebra z-positions, constraints (65-66) prevent vertebra collisions.…”

Section: ) Constrained Finite-time Optimal Control Problem Formulationmentioning

confidence: 99%

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Sabelhaus

Zhao

Zhu

et al. 2021

IEEE Trans. Contr. Syst. Technol.

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“…The natural compliance and reduced failure modes of tensegrity structures have motivated the development of multiple tensegrity robot forms [1]. Some examples include spherical robots designed for locomotion on rugged terrain [4], [5], [6], snakelike robots that crawl along the ground [7], and assistive elements in walking quadrupedal robots [8], [9], [10].…”

Section: Prior Researchmentioning

confidence: 99%

Inclined surface locomotion strategies for spherical tensegrity robots

Chen

Cera

Zhu

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents a new teleoperated spherical tensegrity robot capable of performing locomotion on steep inclined surfaces. With a novel control scheme centered around the simultaneous actuation of multiple cables, the robot demonstrates robust climbing on inclined surfaces in hardware experiments and speeds significantly faster than previous spherical tensegrity models. This robot is an improvement over other iterations in the TT-series and the first tensegrity to achieve reliable locomotion on inclined surfaces of up to 24 • . We analyze locomotion in simulation and hardware under single and multicable actuation, and introduce two novel multi-cable actuation policies, suited for steep incline climbing and speed, respectively. We propose compelling justifications for the increased dynamic ability of the robot and motivate development of optimization algorithms able to take advantage of the robot's increased control authority.

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“…Five different actuated spherical tensegrity robots have been developed within this collaboration: the SUPERball at NASA Ames [15], the TT-1 and TT-2 robots at UC Berkeley [7,8], the TT-3 robot at UC Berkeley [5] (Fig. 2), and the new TT-4 mini first presented here ( Fig.…”

Section: Tensegrity Robots At the Best Lab And Nasa Ames Research Centermentioning

confidence: 99%

“…These robots consist of rigid elements held together in a network of cables in tension. As designed for use in space, tensegrity robots can be made as spheres that roll on a variety of terrains [6,7,8,9,10,11], snake-like robots which crawl along the ground [12,13,14], or as part of walking four-legged robots [15,16,17]. All of these robots are designed to exploit the various beneficial properties of tensegrity structures: low mass, variable stiffness [1], redundancy to failure [18], among other benefits.…”

Section: Introduction and Prior Researchmentioning

confidence: 99%

Modular Elastic Lattice Platform for Rapid Prototyping of Tensegrity Robots

Chen

Daly

Sabelhaus

et al. 2017

Volume 5B: 41st Mechanisms and Robotics Conference

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This paper presents a new platform for prototyping tensegrity robots that uses an elastic lattice structure for the robots' tension network. This approach significantly reduces the time required for design, manufacturing, and assembly, while increasing experimental repeatability and symmetry of the tensioned robot. The platform allows more scientific experiments to be performed in less time and with higher quality.This lattice platform, with associated laser-cutting design techniques developed in this work, has been applied to three types of tensegrity structures: 6-bar spheres, 12-bar spheres, and multiple-vertebra tensegrity spines. For the 12-bar tensegrity case in particular, this new lattice platform has allowed multiple different shapes to be explored as designs for future robots. Basic testing confirmed a reduction in robot assembly time from multiple hours down to a mean of one-two minutes for the 6-bar prototype, five-ten minutes for the various 12-bar prototypes, and approximately seven minutes for the spine.

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Robust learning of tensegrity robot control for locomotion through form-finding

Cited by 39 publications

References 10 publications

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Inclined surface locomotion strategies for spherical tensegrity robots

Modular Elastic Lattice Platform for Rapid Prototyping of Tensegrity Robots

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