Hierarchical and Safe Motion Control for Cooperative Locomotion of Robotic Guide Dogs and Humans: A Hybrid Systems Approach
| Autor: | Aaron D. Ames, Vinay R. Kamidi, Alexander Leonessa, Kaveh Akbari Hamed, Wen-Loong Ma |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
State variable Control and Optimization Computer science Biomedical Engineering 02 engineering and technology Nonlinear control Computer Science::Robotics 020901 industrial engineering & automation Exponential stability Artificial Intelligence Control theory 0202 electrical engineering electronic engineering information engineering FOS: Mathematics Quadratic programming Mathematics - Optimization and Control Robot kinematics Mechanical Engineering 020207 software engineering Motion control Optimal control Computer Science Applications Human-Computer Interaction Nonlinear system Control and Systems Engineering Optimization and Control (math.OC) Hybrid system Robot Computer Vision and Pattern Recognition |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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