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Hybrid-state driven autonomous control for planar bipedal locomotion

机译:平面双足运动的混合状态驱动自主控制

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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. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文的重点是在混合动力框架中为平面双足机器人开发受人类启发的自主控制方案,以实现投射到矢状面上的类人步行。此外,针对两足动物动力学提出了统一的建模方案,该模型结合了由于脚-地面接触状态,单侧地面接触力,接触摩擦锥,与浮动基座相关的被动动力学等因素而引起的各种运动约束的影响脚后跟撞击事件的撞击速度图。自主控制综合被公式化为两级分层控制算法,在外层具有基于混合状态的监督控制,在内层具有一组受约束的运动控制原语的集成集合,称为任务层控制。监督级别控制是基于人为启发式启发式方法设计的,而任务级别控制则被设计为具有线性约束的二次优化问题。根据两足动物的反向动力学模型,依次使用根据关节加速度和地面接触力获得的显式解析解来生成关节扭矩命令。所提出的控制器框架被称为混合状态驱动自主控制(HyDAC)。与许多其他双足控制方案不同,HyDAC不需要针对关节变量进行运动控制的预先计划的轨迹或轨道。而且,它建立在一组基本的运动控制原语上,这些原语与人的行走相似,为控制器提供了透明且易于适应的结构。这些功能使HyDAC框架适用于在台阶和坡度不连续的地形上进行双足步行,而无需先验步态优化。通过对12个链接的两足动物进行动态模型仿真,证明了该控制方案的稳定性和敏捷性,该两足动物的大小和质量特性与被限制在矢状面的成人大小的人相似。仿真结果表明,平面两足动物能够在水平地形上以0.1-2 m / s的速度范围行走,并且以1 m / s的速度在+/- 20度的地面坡度范围内行走。 (C)2016 Elsevier B.V.保留所有权利。

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