Donald A. Sofge

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This paper proposes a reactive motion-planning approach for persistent surveillance of risk-sensitive areas by a team of unmanned aerial vehicles (UAVs). The planner, termed PARCov (Planner for Autonomous Risk-sensitive Coverage), seeks to: i) maximize the area covered by sensors mounted on each UAV; ii) provide persistent surveillance; iii) maintain high(More)
One of the great challenges of putting humanoid robots into space is developing cognitive capabilities for the robots with an interface that allows human astronauts to collaborate with the robots as naturally and efficiently as they would with other astronauts. In this joint effort with NASA and the entire Robonaut team we are integrating natural language(More)
This paper proposes a path-planning approach to enable a team of unmanned aerial vehicles (UAVs) to efficiently conduct surveillance of sensitive areas. The proposed approach, termed PARCov (Planner for Autonomous Risk-sensitive Coverage), seeks to maximize the area covered by the sensors mounted on each UAV while maintaining high sensor data quality and(More)
Traditional social science research has been unable to satisfactorily aggregate individual level data to group, organization and systems levels, making it one of social science’s biggest challenges, if not the most important (Giles, 2011). For game and social theory, we believe that the fault can be attributed to the lack of valid distance measures (e.g.,(More)
In this report we address the role of trust in autonomous systems, and our progress in developing a theory of interdependence for the efficient control of hybrid teams and systems composed of robots, machines and humans working interchangeably. Sentient multi-agent systems require an aggregation process like data fusion. But conventional use of fusion for(More)