RI-Small: The design of fault-tolerant robotic systems for robust performance in hazardous/remote environments

RI-Small：容错机器人系统的设计，可在危险/远程环境中实现稳健的性能

• 批准号: 0812437
• 负责人: Anthony Maciejewski
• 金额: $ 39.95万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0812437&HistoricalAwards=false
• 关键词: RI; Small; design; fault; tolerant

The use of robotic systems in remote and/or hazardous environments requires fundamental advances in software to guarantee that such systems will perform safely and reliably, even when component failures are inevitable. The goal of this work is to design intelligent motion coordination software that instills robots with the capability to use information about component failures to assess the impact of these failures on their motion capabilities, compare their current abilities with those required to perform an assigned task, and to implement appropriate behaviors. The design of such failure tolerant robotic systems relies on the proper incorporation of redundancy, and its intelligent control. The criteria of operation include: (a) failures must be anticipated, (b) performance must gracefully degrade in response to component failures and (c) behavior must be failsafe in the presence of catastrophic failures. This project will develop software that is capable of: (1) evaluating the degree of fault tolerance of a robotic system design, (2) improving the fault tolerance of existing robotic systems or determining optimally fault tolerant designs, and (3) operating robotic systems in a fault tolerant manner in anticipation of potential failures and seamlessly transitioning to optimal post-failure control.

在远程和/或危险环境中使用机器人系统需要软件方面的根本进步，以保证此类系统即使在组件故障不可避免的情况下也能安全可靠地运行。 这项工作的目标是设计智能运动协调软件，使机器人能够使用有关组件故障的信息来评估这些故障对其运动能力的影响，将其当前的能力与执行指定任务所需的能力进行比较，并实施适当的行为。 这种容错机器人系统的设计依赖于冗余的正确结合及其智能控制。 操作标准包括：(a) 必须预见到故障，(b) 性能必须在响应组件故障时适度降低，(c) 在出现灾难性故障时行为必须是故障安全的。 该项目将开发的软件能够：（1）评估机器人系统设计的容错程度，（2）提高现有机器人系统的容错能力或确定最佳容错设计，以及（3）以容错方式操作机器人系统，预测潜在故障并无缝过渡到最佳故障后控制。