Collaborative Research: Increasing Capabilities of Heterogeneous Robot Teams through Mutually Beneficial Physical Interactions

协作研究：通过互利的物理交互提高异构机器人团队的能力

• 批准号: 2308654
• 负责人: Melisa Orta Martinez
• 金额: $ 84.61万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308654&HistoricalAwards=false
• 关键词: Collaborative; Research; Increasing; Capabilities; Heterogeneous

Urban Search and Rescue operations after a structure (e.g., a house or apartment building) collapse face complex layouts with unknown hazards, from fires to energized electrical wiring to the possibility of additional cave-ins. These unknowns and safety concerns lead to a slow and considered search process, even though time is one of the greatest predictors of success in rescue operations. Identifying areas where furniture or debris create “void pockets” for survivors and checking the safety of the structure for rescuers are some of the most laborious and time consuming tasks. Groups of robots with different abilities could reduce the areas to search and improve safety for human operators, significantly helping search efforts in these environments. This award supports research into the development of heterogeneous robot teams to aid in these search and rescue operations. The researchers will create methods for robots of different sizes, shapes, and abilities to physically work together in symbiotic teams and help each other move around collapsed environments. Small tennis-ball-sized robots that can fit through gaps will be delivered to important search areas by plant-inspired growing robots, and the smaller robot will help the larger growing robot steer, sense, and communicate. The lessons learned from building and studying this symbiotic robot team will help future designs for physically symbiotic robots and will serve as a starting point for developing new search and rescue tools. This research investigates the development of symbiotic heterogeneous robot teams which use mutually beneficial physical interactions between team members to share existing capabilities and build new ones. The researchers will leverage two existing robot architectures, soft growing robots and microrobots, with complementary capabilities in the area of navigation and exploration of unstructured environments, and will study how physical interactions between these robots may be designed to create new symbiotic capabilities. While prior work has focused on how robots of differing capabilities can improve team performance compared to homogeneous teams, little work has demonstrated how heterogeneous robots may augment each other's capabilities when they function together. This project directly investigates how these symbiotic behaviors may be designed so that heterogeneous robot teams can be greater than the sum of their parts, with a specific target of creating teams to search disaster environments. In particular, the work will highlight how i) soft growing robots can serve as tethers and structures to extend the reach of microrobots and ii) how microrobots with different payloads can act as changeable actuation, sensing, and communication modules for expanding a growing robot’s range of motion and capabilities. The researchers will prototype and study a diverse range of potential interaction styles while identifying and designing those interactions that will best improve the ability of the team to move in simulated unstructured areas. Overall, the research investigates interactions between highly diverse soft and rigid robots, bridging the gaps between these fields to explore how benefits from each can be leveraged to create more effective robotic teams that can better move around the unstructured world. These results will build towards robot teams which can improve safety and success of search and rescue teams in collapsed buildings.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.

建筑物（例如房屋或公寓楼倒塌）后的城市搜索和救援行动面临着复杂的布局和未知的危险，从火灾到通电电线再到可能发生的额外塌陷，这些未知因素和安全问题导致缓慢且危险的救援。尽管时间是救援行动成功的最大预测因素之一，但识别家具或碎片为幸存者造成“空洞”的区域以及为救援人员检查结构的安全性是最费力和最耗时的搜索过程。具有不同能力的机器人组可以减少搜索区域并提高人类操作员的安全性，从而极大地帮助这些环境中的搜索工作，该奖项支持开发异构机器人团队以帮助这些搜索和救援行动。将为不同尺寸、形状和能力的机器人创造方法，让它们在共生团队中一起工作，并帮助彼此在倒塌的环境中移动。可以穿过间隙的小型网球大小的机器人将被工厂运送到重要的搜索区域。 - 受启发的成长型机器人和较小的机器人将帮助更大的成长型机器人进行驾驶、感知和交流。从构建和研究这个共生机器人团队中学到的经验教训将有助于未来物理共生机器人的设计，并将作为开发新的搜索和救援工具的起点。开发共生异构机器人团队，利用团队成员之间互惠互利的物理互动来共享现有能力并构建新能力，研究人员将利用两种现有的机器人架构，即软体生长机器人和微型机器人，在导航领域具有互补的能力。以及对非结构化的探索环境，并将研究如何设计这些机器人之间的物理交互来创造新的共生能力。虽然之前的工作重点是与同质团队相比，不同能力的机器人如何提高团队绩效，但很少有工作证明异构机器人如何增强每个机器人的能力。该项目直接研究如何设计这些共生行为，以便异构机器人团队可以大于其各个部分的总和，具体目标是创建团队来搜索灾难环境。将突出显示如何i) 软体生长机器人可以作为绳索和结构来扩展微型机器人的活动范围，ii) 具有不同有效负载的微型机器人如何充当可变驱动、传感和通信模块，以扩大生长机器人的运动范围和能力。原型并研究各种潜在的交互方式，同时识别和设计那些最能提高团队在模拟非结构化区域中移动的能力的交互方式。总体而言，该研究研究了高度多样化的软机器人和刚性机器人之间的交互。弥合这些领域之间的差距，探索如何利用每个领域的优势来创建更有效的机器人团队，以便更好地在非结构化世界中移动。这些结果将建立机器人团队，从而提高倒塌中搜救团队的安全性和成功率。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。