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Hybrid-state driven autonomous control for planar bipedal locomotion
Affiliation:1. INESC TEC - INESC Technology and Science, R. Dr. Roberto Frias s/n, 4200-465 Porto, Portugal;2. IEETA - Institute of Electronics and Informatics Engineering of Aveiro, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal;3. Facultad de Ingeniería en Electricidad y Computación, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo, Km 30.5 vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador;4. Computer Vision Center, Campus UAB, 08193 Bellaterra, Barcelona, Spain;5. FEUP - Faculty of Engineering, University of Porto, R. Dr. Roberto Frias s/n, 4200-465 Porto, Portugal;1. Mayo Clinic Division of Hematology, Rochester, MN, USA;2. Mayo Clinic College of Medicine and Mayo Foundation, Rochester, MN, USA;1. Electrical and Computer Engineering department, University of Waterloo, Waterloo, Canada;2. Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada;1. Delft Center for Systems and Control, Delft University of Technology, Delft, 2628 CD, the Netherlands;2. Department of Transport & Planning, Delft University of Technology, Delft, 2600 GA, the Netherlands
Abstract:The focus of this paper is on the development of a human inspired autonomous control scheme for a planar bipedal robot in a hybrid dynamical framework to realize human-like walking projected onto sagittal plane. In addition, a unified modelling scheme is presented for the biped dynamics incorporating the effects of various locomotion constraints due to varying feet-ground contact states, unilateral ground contact force, contact friction cone, passive dynamics associated with floating base etc. along with a practical impact velocity map on heel strike event. The autonomous control synthesis is formulated as a two-level hierarchical control algorithm with a hybrid-state based supervisory control in outer level and an integrated set of constrained motion control primitives, called task level control, in inner level. The supervisory level control is designed based on a human inspired heuristic approach whereas the task level control is formulated as a quadratic optimization problem with linear constraints. The explicit analytic solution obtained in terms of joint acceleration and ground contact force is used in turn to generate the joint torque command based on inverse dynamics model of the biped. The proposed controller framework is named as Hybrid-state Driven Autonomous Control (HyDAC). Unlike many other bipedal control schemes, HyDAC does not require a preplanned trajectory or orbit in terms of joint variables for locomotion control. Moreover, it is built upon a set of basic motion control primitives similar to those in human walk which provides a transparent and easily adaptable structure for the controller. These features make HyDAC framework suitable for bipedal walk on terrain with step and slope discontinuities without a priori gait optimization. The stability and agility of the proposed control scheme are demonstrated through dynamic model simulation of a 12-link planar biped having similar size and mass properties of an adult sized human being restricted to sagittal plane. Simulation results show that the planar biped is able to walk for a speed range of 0.1–2 m/s on level terrain and for a ground slope range of +/?20 deg for 1 m/s speed.
Keywords:Planar biped  Autonomous control  Hybrid event state  Aperiodic stability  Impact velocity map  Motion control primitive
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