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Hierarchical and Safe Motion Control for Cooperative Locomotion of Robotic Guide Dogs and Humans: A Hybrid Systems Approach

Hamed, Kaveh Akbari and Kamidi, Vinay R. and Ma, Wen-Loong and Leonessa, Alexander and Ames, Aaron D. (2019) Hierarchical and Safe Motion Control for Cooperative Locomotion of Robotic Guide Dogs and Humans: A Hybrid Systems Approach. . (Unpublished)

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This paper presents a hierarchical control strategy based on hybrid systems theory, nonlinear control, and safety-critical systems to enable cooperative locomotion of robotic guide dogs and visually impaired people. We address high-dimensional and complex hybrid dynamical models that represent collaborative locomotion. At the high level of the control scheme, local and nonlinear baseline controllers, based on the virtual constraints approach, are designed to induce exponentially stable dynamic gaits. The baseline controller for the leash is assumed to be a nonlinear controller that keeps the human in a safe distance from the dog while following it. At the lower level, a real-time quadratic programming (QP) is solved for modifying the baseline controllers of the robot as well as the leash to avoid obstacles. In particular, the QP framework is set up based on control barrier functions (CBFs) to compute optimal control inputs that guarantee safety while being close to the baseline controllers. The stability of the complex periodic gaits is investigated through the Poincare return map. To demonstrate the power of the analytical foundation, the control algorithms are transferred into an extensive numerical simulation of a complex model that represents cooperative locomotion of a quadrupedal robot, referred to as Vision 60, and a human model. The complex model has 16 continuous-time domains with 60 state variables and 20 control inputs.

Item Type:Report or Paper (Discussion Paper)
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Ames, Aaron D.0000-0003-0848-3177
Additional Information:The work of K. Akbari Hamed amd V. R. Kamidi is supported by the National Science Foundation (NSF) under Grant Number 1637704/1854898. The work of A. D. Ames is supported by the NSF under Grant Numbers 1544332, 1724457, and 1724464 as well as Disney Research LA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NSF.
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Record Number:CaltechAUTHORS:20190626-133626148
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96743
Deposited By: Tony Diaz
Deposited On:26 Jun 2019 20:50
Last Modified:26 Jun 2019 20:50

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