Abstract:

Abstract: The objective of this research is to develop the theory, hardware and computational infrastructure that will enable automatically transforming user-defined, high-level tasks into correct, low-level perception informed control and configurations for modular robots.

Abstract: This poster presents progress of the synergistic framework and algorithms development for a group sensors to collaborate in disaster scenarios. A number of fundamental research results were obtained on scene understanding in a network of visual sensors. These were experimentally evaluated, and datasets and results from these evaluations have been released to the community.

Abstract: The objective of this research is to develop the theory, hardware and computational infrastructure that will enable automatically transforming user-defined, high-level tasks into correct, low-level perception informed control and configurations for modular robots.

Abstract: Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid.

Abstract:  The objective of this project is to improve the performance of autonomous systems in dynamic environments, such as disaster recovery, by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.