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Constraint-based Task Specification and Estimation for Sensor-Based Robot Systems in the Presence of Geometric Uncertainty

机译:存在几何不确定性的基于传感器的机器人系统基于约束的任务指定和估计

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摘要

This paper introduces a systematic constraint-based approach to specify complex tasks of general sensor-based robot systems consisting of rigid links and joints. The approach integrates both instantaneous task specification and estimation of geometric uncertainty in a unified framework. Major components are the use of feature coordinates, defined with respect to object and feature frames, which facilitate the task specification, and the introduction of uncertainty coordinates to model geometric uncertainty. While the focus of the paper is on task specification, an existing velocity- based control scheme is reformulated in terms of these feature and uncertainty coordinates. This control scheme compensates for the effect of time varying uncertainty coordinates. Constraint weighting results in an invariant robot behavior in case of conflicting constraints with heterogeneous units. The approach applies to a large variety of robot systems (mobile robots, multiple robot systems, dynamic human-robot interaction, etc.), various sensor systems, and different robot tasks. Ample simulation and experimental results are presented.
机译:本文介绍了一种基于系统约束的方法来指定由刚性链接和关节组成的常规基于传感器的机器人系统的复杂任务。该方法在一个统一的框架中集成了即时任务说明和几何不确定性的估计。主要组件是使用相对于对象和特征框架定义的特征坐标,这些特征坐标有助于任务规范,以及引入不确定性坐标以对几何不确定性进行建模。尽管本文的重点是任务说明,但根据这些特征和不确定性坐标重新定义了现有的基于速度的控制方案。该控制方案补偿了时变不确定性坐标的影响。在约束与异构单元冲突的情况下,约束加权会导致机器人行为不变。该方法适用于各种各样的机器人系统(移动机器人,多个机器人系统,动态人机交互等),各种传感器系统以及不同的机器人任务。给出了足够的仿真和实验结果。

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