Active balancing and complex motion planning for adult sized humanoid robots

成人尺寸人形机器人的主动平衡和复杂运动规划

• 批准号: 262062-2011
• 负责人: Baltes, Jacky(Hansjorg)
• 金额: $ 1.02万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571221
• 关键词: Active; balancing; complex; motion; planning

The generation of stable walking and motion planning for adult sized (> 1.4m) humanoid robots presents unique challenges, because the state space is high-dimensional, the available sensor feedback is limited, and the robots are underactuated. This proposal aims at investigating new approaches to fundamental problems involving these robots. First, how can we design and implement algorithms so that humanoid robots cannot only move over flat even surfaces, but also move over uneven terrain? The solution to this problem will allow robots to travel across grass surfaces, forest paths, and rugged terrain. Second, how can we develop algorithms so that robots can plan novel motions from scratch rather than having to pre-program them? This will allow humanoid robots to pick up objects, plan its footsteps, and to even climb up a rock wall. Both areas have received significant attention in recent years, and progress has been made - but versatile, robust, practical solutions are still elusive. The research described in this proposal aims at greatly increasing the range of balancing and actions that a robot can execute by allowing some of its movements to be open-loop rather than closed-loop. To overcome the need for highly accurate global models of the kinematics and dynamics of the robot as well as its interaction with the environment, we propose to use multiple models with different resolutions that model specific important parts of the behaviour of the robot. Applying this idea to active balancing will allow us to overcome restrictions imposed by the 3D inverted pendulum model and the zero moment point (ZMP) constraint and to generate more stable, faster, more efficient and more natural looking walking gaits and balancing behaviours. The controller will generate balancing reflexes that will bring an unbalanced robot back into the controllable balanced region. We propose novel motion planning algorithms that uses the controllable balanced regions rather than regions based on kinematic and dynamic constraints as state space for the planning process.

成人尺寸（> 1.4m）人形机器人的稳定行走和运动规划的生成面临着独特的挑战，因为状态空间是高维的，可用的传感器反馈有限，机器人是欠驱动的。该提案旨在研究涉及这些机器人的基本问题的新方法。首先，我们如何设计和实现算法，使人形机器人不仅能在平坦平坦的表面上移动，还能在不平坦的地形上移动？这个问题的解决方案将允许机器人在草地表面、森林小径和崎岖的地形上行走。其次，我们如何开发算法，使机器人可以从头开始规划新的动作，而不必预先编程？这将使人形机器人能够拾取物体，规划其脚步，甚至爬上岩壁。