In addition to navigating confined and unstable spaces, multiple robots—each with different perspectives—would provide improved spatial awareness; new reasoning functions could provide 3-D mapping capabilities.

Morison noted that the system’s success will depend on how well multiple robots can work together as a team. In fact, the group identified multi-robot teamwork as the group’s most significant challenge, citing the current lack of breakthroughs in communications protocols and multi-agent coordination. Effective multi-robot coordination becomes especially critical in post-disaster environments that are often resource limited and unpredictable. Under some circumstances, humans would assume a larger or primary role in coordination efforts—for example, under system failure or when human expertise is required. In cases where humans and robots share responsibilities, automated reasoning would be combined with human reasoning.

Lastly, the group observed that as robots develop increased autonomous capabilities, there may be a push for increased autonomous decision making. The group questioned what if anything might limit such autonomy. For example, what ethical considerations exist for human robot rescue teams (with varying various levels of autonomous capabilities) that triage lost or injured individuals?

Group 2: Team Clean

Moderator: Michael Beetz

Group Member: Michael Beetz, Andreas Hofmann, Mark Neerincx, Liz Sonenberg

Michael Beetz, the moderator, provided a summary of the group’s discussions. Beetz indicated that the group focused its efforts on designing a home robotic cleaning team, “Team Clean,” composed of multiple machines (e.g., humanoid robot, vacuum cleaner, small UAV to “map” the environment), and potentially a human director. The team would be capable of accomplishing a number of tasks with varying degrees of difficulty, from cleaning bathrooms to washing dishes, vacuuming, and doing the laundry.

To do this, a number of research challenges would be addressed, including: practical task manipulation (e.g., picking up fragile objects), smooth locomotion and navigation in a dynamic environment (e.g., going up stairs and opening doors), safety (e.g., not getting in the way of residents or pets), human-robot communication, and social robotics. In addition, machines would have to be able to learn and recover from mistakes and possess sufficient knowledge intensiveness (e.g., to go from an abstract task “to clean up” to understanding how clean is “clean enough”).

Some tasks, Beetz acknowledged, would require varying degrees of interaction between machines and residents. In some cases, a robot may request feedback from the resident. For example, a robot might ask whether a dirty glass

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