Journal ArticleDOI
Learning, planning, and control for quadruped locomotion over challenging terrain
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TLDR
A floating-base inverse dynamics controller that allows for robust, compliant locomotion over unperceived obstacles and the generalization ability of this controller is demonstrated by presenting results from testing performed by an independent external test team on terrain that has never been shown to us.Abstract:
We present a control architecture for fast quadruped locomotion over rough terrain. We approach the problem by decomposing it into many sub-systems, in which we apply state-of-the-art learning, planning, optimization, and control techniques to achieve robust, fast locomotion. Unique features of our control strategy include: (1) a system that learns optimal foothold choices from expert demonstration using terrain templates, (2) a body trajectory optimizer based on the Zero-Moment Point (ZMP) stability criterion, and (3) a floating-base inverse dynamics controller that, in conjunction with force control, allows for robust, compliant locomotion over unperceived obstacles. We evaluate the performance of our controller by testing it on the LittleDog quadruped robot, over a wide variety of rough terrains of varying difficulty levels. The terrain that the robot was tested on includes rocks, logs, steps, barriers, and gaps, with obstacle sizes up to the leg length of the robot. We demonstrate the generalization ability of this controller by presenting results from testing performed by an independent external test team on terrain that has never been shown to us.read more
Citations
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Journal ArticleDOI
CHOMP: Covariant Hamiltonian optimization for motion planning
Matt Zucker,Nathan Ratliff,Anca D. Dragan,Mihail Pivtoraiko,Matthew Klingensmith,Christopher M. Dellin,J. Andrew Bagnell,Siddhartha S. Srinivasa +7 more
TL;DR: CHOMP (covariant Hamiltonian optimization for motion planning), a method for trajectory optimization invariant to reparametrization, uses functional gradient techniques to iteratively improve the quality of an initial trajectory, optimizing a functional that trades off between a smoothness and an obstacle avoidance component.
Journal ArticleDOI
Design of HyQ – a hydraulically and electrically actuated quadruped robot:
Claudio Semini,Nikos G. Tsagarakis,Emanuele Guglielmino,Michele Focchi,Ferdinando Cannella,Darwin G. Caldwell +5 more
TL;DR: In this article, a hydraulically powered quadruped robot (HyQ) was developed to serve as a platform to study not only highly dynamic motions, such as running and jumping, but also careful navigat...
Journal ArticleDOI
Recent Advances in Robot Learning from Demonstration
TL;DR: In the context of robotics and automation, learning from demonstration (LfD) is the paradigm in which robots acquire new skills by learning to imitate an expert.
Journal ArticleDOI
High speed trot-running: Implementation of a hierarchical controller using proprioceptive impedance control on the MIT Cheetah
TL;DR: This paper presents implementation of a highly dynamic running gait with a hierarchical controller on the MIT Cheetah incorporating proprioceptive feedback and programmable virtual leg compliance and achieved a stable trot-running gait in the sagittal plane.
Journal ArticleDOI
Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid
Alexander Herzog,Nicholas Rotella,Sean Mason,Felix Grimminger,Stefan Schaal,Ludovic Righetti +5 more
TL;DR: In this article, a simplification of hierarchical inverse dynamics based on cascades of quadratic programs has been proposed for real-time control of legged robots, where momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior.
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Proceedings ArticleDOI
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Proceedings ArticleDOI
Biped walking pattern generation by using preview control of zero-moment point
Shuuji Kajita,Fumio Kanehiro,Kenji Kaneko,Kiyoshi Fujiwara,Kensuke Harada,Kazuhito Yokoi,Hirohisa Hirukawa +6 more
TL;DR: A new method of a biped walking pattern generation by using a preview control of the zero-moment point (ZMP) is introduced and a preview controller can be used to compensate the ZMP error caused by the difference between a simple model and the precise multibody model.