Geometric Optimal Control for Locomotion of Biologically Inspired Robotic Systems

仿生机器人系统运动的几何优化控制

• 批准号: 1400256
• 负责人: Patricio Vela
• 金额: $ 27万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-15 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1400256&HistoricalAwards=false
• 关键词: Geometric; Optimal; Control; Locomotion; Biologically; Geometric; Optimal; Control; Locomotion; Biologically

Animals, and their analogous biologically-inspired robots out-perform traditional robots (e.g., cars, planes, boats) in many environments and for many tasks. Unfortunately, control of biologically-inspired robots differs from that of traditional robots, preventing their adoption. Achieving control of biologically-inspired robots with the same ease as traditional robots would markedly transform the field of robotics. The main challenge is that locomotion requires time-varying periodic control inputs, known as gaits, to achieve movement. The discrete nature of the gaits and their time-varying structure means that standard control strategies do not apply. It is critical that this class of robots be as simple to control as traditional robots if widespread adoption is to occur. This award supports fundamental research into a mathematical framework that will lead to simpler formulations for control of these robots. The simpler formulation will be of value to society as biologically-inspired robots are envisioned to be of great practical use for a variety of robotic application domains, such as search and rescue, defense, surveillance, and plant integrity inspection. Furthermore, biologically-inspired robots are quite popular with youth and the public. We will capitalize on this appeal to increase and broaden participation in engineering and engineering research.Biologically-inspired robotic systems are typically nonholonomic systems that require time-varying control inputs, making optimal control-based design of trajectories challenging. Further, these systems rely on families of parametrizable, time-varying control inputs, called gaits, to generate movement. Gaits are disjoint controls, in that applying one gait precludes the use of another. Thus, not only must the control input be time-varying, but the reachability properties are gait-dependent and may require switches of control modes for some navigation goals. On account of these challenges, the development of a framework for trajectory generation and planning of these systems is still an open problem. Drawing on concepts from differential geometry, geometric mechanics, and averaging theory to exploit the geometric and temporal symmetries of these robotic systems, a reduced optimal control formulation will be derived. The connection of these concepts to multi-mode, multi-dimensional control systems will be delineated to resolve the switched, optimal control problem associated to systems with multiple gait strategies. To generate initial trajectory estimates for the optimal control solver, we will specialize a kino-dynamic path planning algorithm to incorporate the geometric and multi-gait properties of biologically-inspired robotic systems.

动物及其类似的生物启发的机器人在许多环境和许多任务中都超越了传统机器人（例如汽车，飞机，船）。 不幸的是，对生物学启发的机器人的控制与传统机器人的控制有所不同，从而阻止了其采用。以与传统机器人相同的轻松自然化的机器人来控制生物学启发的机器人，可以显着改变机器人技术领域。 主要的挑战是运动需要时变的周期性控制输入（称为步态）才能实现运动。 步态的离散性质及其时间变化的结构意味着标准控制策略不适用。 如果要进行广泛采用，这类机器人与传统机器人一样易于控制，这一点至关重要。 该奖项支持针对数学框架的基本研究，该研究将导致更简单的机器人控制。 更简单的表述对社会具有价值，因为以生物学灵感的机器人被认为是对各种机器人应用领域（例如搜索和救援，防御，防御，监视和植物完整性检查）具有很大实际用途的。此外，以生物学启发的机器人在青年和公众中非常受欢迎。我们将利用这种吸引力，以增加和扩大对工程和工程研究的参与。生物学启发的机器人系统通常是非虚构的系统，需要时变的控制输入，从而使基于基于控制的轨迹的最佳设计具有挑战性。 此外，这些系统依赖于可参数性的，随时间变化的控制输入（称为步态）来产生运动。步态是不相交的控件，因为应用一个步态阻止了另一个步态的使用。 因此，控制输入不仅必须是时间变化的，而且可达性属性是步态依赖性的，并且可能需要对某些导航目标的控制模式开关。由于这些挑战，开发轨迹生成和计划这些系统的框架仍然是一个开放的问题。 利用从差异几何形状，几何力学和平均理论利用这些机器人系统的几何和时间对称性的概念，将得出减少的最佳控制配方。这些概念与多模式，多维控制系统的连接将被描述，以解决与具有多个步态策略的系统相关的开关，最佳控制问题。为了生成最佳控制求解器的初始轨迹估计值，我们将专门使用一种基诺动态路径计划算法来结合生物启发的机器人系统的几何和多对基质性能。