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Hierarchical Feedback Control for Complex Hybrid Models of Multiagent Legged Robotic Systems

Akbari Hamed, Kaveh and Ma, Wen-Loong and Kamidi, Vinay R. and Ames, Aaron D. (2019) Hierarchical Feedback Control for Complex Hybrid Models of Multiagent Legged Robotic Systems. . (Unpublished)

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This paper presents a hierarchical feedback control strategy for complex hybrid systems that represent collaborative multiagent legged robotic systems with arms for manipulating an object. We develop high-dimensional hybrid models, including continuous- and discrete-time dynamics, for multiagent legged systems. Each agent has its own baseline controller to produce an exponentially stable legged locomotion pattern. For the manipulating purpose of the object, a two-level control strategy is proposed. At the higher level, a model predictive control based convex quadratic programming (QP) computes the required forces to be generated by the end effectors (EEs). The lower-level controllers are then set up based on convex QPs to refine the baseline controllers while generating the prescribed forces at the EEs. Two different strategies for the deployment of the lower-level controllers, including centralized and decentralized algorithms, are proposed. The power of the control algorithms is finally illustrated on an extensive numerical simulation of two quadruped agents (Vision 60 robots) with Kinova arms to steer an object for which the complex hybrid model has 64 continuous-time domains, 132 state variables, and 36 control inputs.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Akbari Hamed, Kaveh0000-0001-9597-1691
Kamidi, Vinay R.0000-0002-4227-6131
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20190626-092917746
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96716
Deposited By: Tony Diaz
Deposited On:26 Jun 2019 16:51
Last Modified:03 Oct 2019 21:24

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