CPS:Medium: Tightly Integrated Perception and Planning in Intelligent Robotics

该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。这项研究的目标是通过一种新的范式开发真正智能的自动驾驶，该范式将概率感知和确定性规划紧密地结合在一个正式的、可验证的框架中。跨学科方法利用三项相互关联的任务。表示法开发了用于构建和维护动态环境的表示法的新技术，以促进更高级别的规划。预测和行动规划开发了预测环境变化的方法，并将其用作规划过程的一部分。可验证任务规划开发了为高级行为提供概率保证的理论和技术。这种方法根深蒂固的是理论和使用内部设备齐全的车辆进行的实验之间的协同。最近的城市挑战赛展示了当前自动驾驶的脆弱性，小的感知错误会传播到规划者身上，导致险些失手和小事故；从根本上说，概率感知和确定性规划之间存在不匹配，导致“被动”而不是“智能”的行为。这项拟议的研究直接解决了这一问题，为智能网络物理系统开发了一个单一的、统一的感知和规划理论。短期内，这项研究可以用于开发先进的汽车安全系统。老年人和身体受损的人将受益于廉价、先进的汽车自动化。从长远来看，先进的智能可能会导致自动化车辆的应用，如合作搜索和救援。该研究计划将通过计算机科学和机械工程的跨学科课程以及体验式学习项目来教育学生。结果将传播给社区，包括代表性不足的学院和大学。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is to develop truly intelligent, automated driving through a new paradigm that tightly integrates probabilistic perception and deterministic planning in a formal, verifiable framework. The interdisciplinary approach utilizes three interlinked tasks. Representations develops new techniques for constructing and maintaining representations of a dynamic environment to facilitate higher-level planning. Anticipation and Motion Planning develops methods to anticipate changes in the environment and use them as part of the planning process. Verifiable Task Planning develops theory and techniques for providing probabilistic guarantees for high-level behaviors. Ingrained in the approach is the synergy between theory and experiment using an in house, fully equipped vehicle.The recent Urban Challenge showed the current brittleness of autonomous driving, where small perception mistakes would propagate into planners, causing near misses and small accidents; Fundamentally, there is a mismatch between probabilistic perception and deterministic planning, leading to "reactive" rather than "intelligent" behaviors. The proposed research directly addresses this by developing a single, unified theory of perception and planning for intelligent cyber-physical systems.Near term, this research could be used to develop advanced safety systems in cars. The elderly and physically impaired would benefit from inexpensive, advanced automation in cars. Far term, the advanced intelligence could lead to automated vehicles for applications such as cooperative search and rescue. The research program will educate students through interdisciplinary courses in computer science and mechanical engineering, and experiential learning projects. Results will be disseminated to the community including under-represented colleges and universities.