Knowledge Resource Center for Ecological Environment in Arid Area
| 项目编号 | 1028237 |
| CDI-TYPE II: Collaborative Research: Cyber-Amplified Bioinspiration in Robotics | |
| Daniel Koditschek | |
| 主持机构 | University of Pennsylvania |
| 开始日期 | 2010-10-01 |
| 结束日期 | 2016-09-30 |
| 资助经费 | 1286200(USD) |
| 项目类别 | Standard Grant |
| 资助机构 | US-NSF（美国国家科学基金会） |
| 项目所属计划 | CDI TYPE II |
| 语种 | 英语 |
| 国家 | 美国 |
| 英文简介 | Intellectual Merit This 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 Impacts Scientifically, 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. |
| 来源学科分类 | Engineering |
| URL | https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028237 |
| 资源类型 | 项目 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/341907 |
| 推荐引用方式 GB/T 7714 | Daniel Koditschek.CDI-TYPE II: Collaborative Research: Cyber-Amplified Bioinspiration in Robotics.2010. |
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