Control of Robust Micro-Robots in Uncertain Environments

不确定环境中鲁棒微型机器人的控制

• 批准号: 1435222
• 负责人: Kenn Oldham
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1435222&HistoricalAwards=false
• 关键词: Control; Robust; Micro; Robots; Uncertain

Autonomous micro-robots a few millimeters in size have transformative potential for applications ranging from infrastructure monitoring to disaster response to exploration of hostile or inaccessible locales. Such tasks will require robots that can successfully navigate complicated and unpredictable terrain and environments. Given limitations on moving parts in micro-scale systems, legged locomotion offers the best combination of adaptability and efficiency. Standard features of full-scale walking robots, such as motorized and instrumented knee and ankle joints, are impossible or impractical to realize with current micro-fabrication techniques, making flexible linkages the most promising approach to articulated limbs. But, because of differences between the ways that leg stiffness and body mass scale as robot dimensions decrease, the natural springiness of the legs cannot be relied on to keep all feet in contact with uneven ground, which can greatly degrade gait effectiveness. These challenges make legged locomotion an essentially different and more difficult problem at the micro-scale. This project will advance the fundamental state of the art towards high-speed, high-mobility legged micro-robots navigating in an uncertain environment. It will develop models of the leg-surface interaction, and use these models to derive efficient and effective walking gaits. To maximize adaptability in changing conditions, internal sensors capable of monitoring gait effectiveness will be added to existing micro-robot leg designs.This project will study the complex contact interaction of walking micro-robots with multiple feet moving at high-speeds on varying surfaces. The resulting dynamic models will be used to identify walking gaits that produce efficient forward motion over a range of environmental conditions. The investigators have previously combined thin-film lead-zirconate-titanate (PZT) with resilient polymer materials to demonstrate micro-fabricated legs with an unusually large range of motion and actuation speed. In this project, sensing elements will be integrated into the thin-film PZT/polymer legs to allow basic estimation of robot motion. Actuation and estimator design will meet constraints imposed by small-scale power sources, through input sequences based on a limited number of switched input voltages and leg and robot movement estimates based on limited sensor samples. Once estimation of robot walking effectiveness has been demonstrated using on-chip measurements, adaptive control algorithms will be tailored to respond to environmental conditions that change over time.

几毫米大小的自主微型机器人具有变革性的应用潜力，从基础设施监测到灾难应对，再到探索敌对或无法进入的地区。这些任务需要机器人能够成功地在复杂和不可预测的地形和环境中航行。考虑到微尺度系统中运动部件的限制，腿式运动提供了适应性和效率的最佳组合。全尺寸步行机器人的标准特征，例如电动和仪器化的膝关节和踝关节，用当前的微制造技术是不可能或不切实际的，这使得柔性联动装置成为最有前途的铰接肢体方法。但是，由于腿部刚度和身体质量随机器人尺寸减小而缩放的方式之间的差异，不能依靠腿部的自然弹性来保持所有脚与不平坦的地面接触，这会大大降低步态效率。这些挑战使得腿部运动在微观尺度上成为一个本质上不同且更困难的问题。该项目将推进高速，高机动性腿式微型机器人在不确定环境中导航的基本技术水平。它将开发腿表面相互作用的模型，并使用这些模型来获得高效和有效的步行步态。为了最大限度地适应不断变化的条件，能够监测步态有效性的内部传感器将被添加到现有的微型机器人腿设计中。本项目将研究步行微型机器人的复杂接触相互作用，该机器人具有多个脚，在不同的表面上高速移动。由此产生的动态模型将被用来确定步行步态，产生有效的向前运动在一系列的环境条件。研究人员先前将薄膜锆钛酸铅（PZT）与弹性聚合物材料相结合，以展示具有异常大的运动范围和致动速度的微制造腿。在这个项目中，传感元件将被集成到薄膜PZT/聚合物腿，使机器人运动的基本估计。驱动器和估计器的设计将满足小规模电源的限制，通过输入序列的基础上有限数量的开关输入电压和腿和机器人运动的估计有限的传感器样本的基础上。一旦使用片上测量证明了机器人行走效率的估计，自适应控制算法将被定制以响应随时间变化的环境条件。