CAREER: Dynamic Locomotion with Plasticity for Remote Sensing in Crawlspaces

爬行空间无处不在：洞穴、喀斯特景观、竖井、管道、压载舱、管道和谷物升降机。来自这些环境的数据具有巨大的科学（生物多样性和地质过程）、社会（考古和文化遗迹）、环境（自然资源和矿藏）和健康-安全-经济（资产管理和监测）意义。然而，在爬行空间中的人类操作是昂贵的、缓慢的和有风险的。现有的蛇和昆虫机器人可以在管道中爬行，并在厘米级的空间内操作;然而，它们太慢或不完全自主。迫切需要专门为爬行空间设计的快速，敏捷和高效的自主系统。腿部运动和多旋翼飞行显示出解决这一挑战的希望，已经通过超越任何其他机器人类别的能力彻底改变了许多遥感任务。然而，它们的运行仍然局限于宽敞的隧道。该学院早期职业发展（CAREER）项目支持旨在利用腿式和旋翼机器人的卓越敏捷性，效率和速度的研究，并专门将其用于爬行空间。该项目设计了一种多模态机器人，具有广泛的运动可塑性，能够通过双足行走和飞行灵活地有效穿越非常狭窄的爬行空间。此外，该项目旨在促进东北大学机器人项目中的性别平等，这是学校领导确定的一个重要增长领域。在爬行空间中实现高效，敏捷和快速的腿部空中运动代表了机器人运动的新进展。在桥接爬行空间中的腿式运动和多旋翼飞行方面仍然存在三个知识差距：（1）当从为开放空间设计的腿式机器人过渡到在爬行空间中操作的较小机器人时，致动挑战阻碍运动控制性能的可扩展性，这是快速和精确的足部放置所必需的;（2）由表面附近的多旋翼空气喷射引起的不稳定性问题造成飞行固定风险;（3）爬行空间需要多种运动模式，并且没有系统的机器人设计框架来适应这些模式所规定的要求。该项目将从事基础研究，以解决这些差距，设计一个生物启发的运动机器人能够行走，悬停，跳跃，并在倾斜的表面上运行，以推动移动的机器人的操作范围，使非常狭窄的爬行空间内的自主操作成为可能。该项目的努力围绕机器人和控制设计。该项目的主要创新领域包括：（1）引入基于计算结构设计的小型机器人驱动设计范例，以实现与大型机器人相当的运动控制性能;（2）研究和验证新的运动特性和基础模型以及基于姿态操纵和推力矢量集成的非线性控制器，以克服空中机器人中的喷气风险;（3）通过生成式设计方法共同设计机器人和控制装置，以适应多种运动模式所带来的相互冲突的要求。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Crawlspaces are everywhere: caves, karst landscapes, shafts, ducts, ballast tanks, pipes, and grain elevators. Data from these environments holds immense scientific (biodiversity and geological processes), societal (archaeological and cultural remains), environmental (natural resources and mineral deposits), and health-security-economical (asset management and monitoring) significance. However, human operation in crawlspaces is costly, slow, and risky. Existing snake and insect robots can crawl in pipes and operate within centimeter-scale spaces; however, they are too slow or not completely autonomous. There is a pressing need for fast, agile, and efficient autonomous systems specifically designed for crawlspaces. Legged locomotion and multi-rotor flight show promise in addressing this challenge, having already revolutionized numerous remote sensing tasks by surpassing the capabilities of any other robot category. However, their operation remains limited to spacious tunnels. This Faculty Early Career Development (CAREER) project supports research that seeks to harness the exceptional agility, efficiency, and speed of legged and rotary-wing robots and adapt it specifically for use in crawlspaces. The project designs a multi-modal robot with extensive locomotion plasticity capable of efficiently traversing extremely tight crawlspaces with agility through bipedal walking and flying. Furthermore, this project aims to promote gender equity in Northeastern University’s robotics program, a significant area of growth identified by school leadership.Achieving efficient, agile, and fast legged-aerial locomotion in crawlspaces represents a new advancement in robot locomotion. Three knowledge gaps still exist in bridging legged locomotion and multi-rotor flight in crawlspaces: (1) Actuation challenges hinder the scalability of motion control performance, necessary for fast and precise foot placement, when transitioning from legged robots designed for open spaces to smaller robots operating in crawlspaces; (2) Instability issues arising from multi-rotors’ air jets near surfaces pose flight immobilization risks; (3) Crawlspaces need several modes of locomotion and there is no systematic robot design framework to accommodate the requirements dictated by these modes. This project will engage in fundamental research to address these gaps, designing a bioinspired locomotion robot capable of walking, hovering, jumping, and running over inclined surfaces to push the operational envelope of mobile robots, making autonomous operations inside extremely tight crawlspaces possible. The project’s efforts revolve around robot and control design. This project’s key areas of innovation include (1) Introducing actuation design paradigms for small robots based on computational structure design for achieving comparable motion control performance seen in large robots; (2) Research and validation of new locomotion feats and underlying models and nonlinear controllers based on the integration of posture manipulation and thrust vectoring to overcome air jet risks in aerial robotics; (3) Co-designing robots and controls through generative design methods to accommodate conflicting requirements imposed by many locomotion modes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.