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Toward simple control for complex, autonomous robotic applications: combining discrete and rhythmic motor primitives

机译:面向复杂,自主机器人应用的简单控制:结合离散和有节奏的电机原语

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摘要

Vertebrates are able to quickly adapt to new environments in a very robust, seemingly effortless way. To explain both this adaptivity and robustness, a very promising perspective in neurosciences is the modular approach to movement generation: Movements results from combinations of a finite set of stable motor primitives organized at the spinal level. In this article we apply this concept of modular generation of movements to the control of robots with a high number of degrees of freedom, an issue that is challenging notably because planning complex, multidimensional trajectories in time-varying environments is a laborious and costly process. We thus propose to decrease the complexity of the planning phase through the use of a combination of discrete and rhythmic motor primitives, leading to the decoupling of the planning phase (i.e. the choice of behavior) and the actual trajectory generation. Such implementation eases the control of, and the switch between, different behaviors by reducing the dimensionality of the high-level commands. Moreover, since the motor primitives are generated by dynamical systems, the trajectories can be smoothly modulated, either by high-level commands to change the current behavior or by sensory feedback information to adapt to environmental constraints. In order to show the generality of our approach, we apply the framework to interactive drumming and infant crawling in a humanoid robot. These experiments illustrate the simplicity of the control architecture in terms of planning, the integration of different types of feedback (vision and contact) and the capacity of autonomously switching between different behaviors (crawling and simple reaching).
机译:脊椎动物能够以非常健壮,轻松的方式快速适应新环境。为了解释这种适应性和鲁棒性,神经科学中非常有前途的观点是产生运动的模块化方法:运动是由在脊椎水平组织的有限的一组稳定运动原语的组合产生的。在本文中,我们将运动的模块化生成这一概念应用于具有高度自由度的机器人的控制中,这一问题尤其具有挑战性,因为在时变环境中规划复杂的多维轨迹是一项费力且昂贵的过程。因此,我们建议通过使用离散的和有节奏的运动原语的组合来降低计划阶段的复杂性,从而导致计划阶段(即行为的选择)与实际轨迹生成的分离。这样的实现通过减小高级命令的维数来简化对不同行为的控制以及在不同行为之间的切换。此外,由于电机原语是由动力系统生成的,因此可以通过高级命令更改当前行为,或者通过感官反馈信息以适应环境限制,来平滑地调制轨迹。为了展示我们方法的通用性,我们将该框架应用于人形机器人中的交互式鼓和婴儿爬行。这些实验从计划的角度,不同类型的反馈(视觉和接触)的集成以及不同行为之间的自主切换(爬行和简单到达)的能力方面说明了控制体系结构的简单性。

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