CDI-Type II: Collaborative Research: Cyber-Amplified Bioinspiration in Robotics

该项目结合了认知心理学、计算视觉和学习、神经机械系统生物学和机器人技术的结果和方法，开发了一个计算机辅助环境，用于研究动物的感觉运动策略，发现它们如何强化动物的认知能力，并利用这些见解激发机器人导航、定位和态势感知的新算法。我们观察活的，完整的，高度移动的陆地无脊椎食肉动物，如鬼蟹，沙漠蝎子和虎甲虫，在精心建造的栖息地，挑战他们的能力，以适应地形和导航空间。我们从视觉、肌肉、神经和生物力学记录的大量并行实时记录中自动收集、注释和提取它们的行为的数学模型。我们挖掘这些数据集，以发展直观的假设，以及这些动物组织自己的感觉运动数据流的基础的形式化数学表示，以在自主心理发展过程中从先前巩固的成分中编译新的行为。我们将许多现有的传感器套件添加到高度敏捷的现有机器人体内，并通过算法实例化假设的动物模型，以开发支持或反驳挑战和改进它们的证据。更广泛的影响科学上，我们在相互关系中发现的新的计算工具和思想，我们建立了一座桥梁，连接了长期以来被时空尺度划分的整个学科领域，以及随之而来的分析传统、术语和方法上的差距。例如，对更简单物种的这些复杂能力的研究，为与人类关系更密切的物种的认知构建提供了新的视角。从技术发明的角度来看，在这项研究中开创的算法可以赋予机器类似动物的品质。在参与其环境，甚至在非结构化世界中其整体态势感知的近端韧性。例如，该团队受到启发，想象一个具有鬼蟹（可执行任务）能力的搜救机器人会是什么样子。从培训和教育的角度来看，在这个项目中开发的自动化数据库收集和管理工具为大众带来了概念和计算构建块，这些构建块迄今为止一直是一小群专家的专属领域。例如，一个普遍可访问的（基于云的）工具，用于统一机器人和动物的设计、解析、显示和交叉比较，可以从最亲密的到最广泛的设计和操作范围随意搜索，这将对许多不同层次的教师的能力产生深远的影响，从而激发合成科学和生物科学的魅力和统一性。

Intellectual MeritThis project mixes results and methods from cognitive psychology, computational vision and learning, neuromechanical systems biology, and robotics to develop a computer assisted environment for studying animal sensorimotor strategies, discovering how they undergird animal cognitive capabilities, and using those insights to inspire new algorithms for robot navigation, localization and situational awareness. We observe live, intact, highly mobile terrestrial invertebrate predators such as ghost crabs, desert scorpions and tiger beetles in carefully constructed habitats that challenge their ability to negotiate terrain and navigate space. We automate the collection, annotation and mathematical model extraction of their behavior from massive, parallel real-time recordings of visual, muscle, neural, and biomechanical recordings. We mine these data sets to develop intuitive hypotheses as well as formal mathematical representations of the basis on which these animals organize their own sensorimotor data streams to compile novel behaviors from previously consolidated constituents in a process of autonomous mental development. We add numerous existing sensor suites to highly agile existing robot bodies and instantiate algorithmically the hypothesized animal models to develop supporting or refuting evidence that challenges and refines them.Broader ImpactsScientifically, the new computational tools and ideas we identify in the interrelations we set up promise a bridge between whole areas of disciplines that have long been divided by spatiotemporal scale and the concomitant gap in analytical tradition, terminology and methods. For example, the study of these complex competencies in simpler species offers a new glimpse at the building blocks of cognition in species more closely related to humans. From the perspective of technological invention, algorithms pioneered in this research could lend an animal-like quality to a machine?s proximal tenacity in engaging its environment and even its overall situational awareness within unstructured worlds. For example, the team is inspired to imagine what it might be like to have a search and rescue robot with the (taskable) capabilities of a ghost crab. From the perspective of training and education, the automated database collection and management tools developed in this project bring to a mass audience the conceptual and computational building blocks that have heretofore been the exclusive province of a small group of experts. For example, a universally accessible (?cloud-based?) tool for unifying the design, parsing, display, and cross comparison of robots and animals searchable at will from the most intimate to the broadest scale of design and operation would have a profound impact on the ability of teachers at many different levels to motivate the fascination and unity of both synthetic and biological science.