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The authors examine the roles of robots for childcare applications. They cite the argument of N. Sharkey and A. Sharkey on the ethical aspect of robot nannies and presents counter argument. They mention that there are many reasons why childcare robotics could lead to neglect on the part of the parents but the matter is not only for robots. They also suggest that parents, roboticists, and legislators should remain vigilant about ethical issues.

The article focuses on the interdisciplinary research that study the human-robot interaction for socially assistive robotic applications. The robotics community is trying to create robots capable of exhibiting social qualities. The field has aimed on the use of the robot's physical embodiment to communicate and interact with users in a social manner. Furthermore, the principle application domains of socially assistive robotics is discussed.

We study the problem of achieving global behavior in a group of distributed robots using only local sensing and minimal communication, in the context of formations. The goal is to have N mobile robots establish and maintain some predetermined geometric shape. We report results from extensive simulation experiments, and 40+ experiments with four physical robots, showing the viability of our approach. The key idea is that each robot keeps a single friend at a desired angle θ, using some appropriate sensor. By panning the sensor by θ degrees, the goal for all formations becomes simply to center the friend in the sensor's field of view. We also present a general analytical measure for evaluating formations and apply it to the position data from both simulation and physical robot experiments. We used two lasers to track the physical robots to obtain ground truth validation data. [ABSTRACT FROM AUTHOR]

The key to utilizing the potential of multirobot systems is cooperation. How can we achieve cooperation in systems composed of failure-prone autonomous robots operating in noisy, dynamic environments? In this paper, we present a novel method of dynamic task allocation for groups of such robots. We implemented and tested an auction-based task allocation system which we call MURDOCH, built upon a principled, resource centric, publish/subscribe communication model. A variant of the Contract Net Protocol, MURDOCH produces a distributed approximation to a global optimum of resource usage. We validated MURDOCH in two very different domains: a tightly coupled multirobot physical manipulation task and a loosely coupled multirobot experiment in long-term autonomy. The primary contribution of this paper is to show empirically that distributed negotiation mechanisms such as MURDOCH are viable and effective for coordinating physical multirobot systems. [ABSTRACT FROM AUTHOR]

We describe localization-space trails (LOST), a method that enables a team of robots to navigate between places of interest in an initially unknown environment using a trail of landmarks. The landmarks are not physical; they are waypoint coordinates generated online by each robot and shared with teammates. Waypoints are specified in each robot's local coordinate system, and contain references to features in the world that are relevant to the team's task and common to all robots. Using these task-level references, robots can share waypoints without maintaining a global coordinate system. The method is tested in a series of real-world multirobot experiments. The results demonstrate that the method: 1) copes with accumulating odometry error; 2) is robust to the failure of individual robots; 3) converges to the best route discovered by any robot in the team. In one experiment, a team of four autonomous mobile robots performs a resource transportation task in our uninstrumented ofrice building. Despite significant divergence of their local coordinate systems, the robots are able to share waypoints, forming and following a common trail between two predetermined locations for more than three hours, traveling a total of 8.2 km (5.1 miles) before running out of power. Designed to scale to large populations, LOST is fully distributed, with low costs in processing, memory, and bandwidth. It combines metric data about the position of features in the world with instructions on how to get from one place to another; producing something between a map and a plan. [ABSTRACT FROM AUTHOR]

Presents a behavior-based approach to structuring and controlling complex robotic systems in the U.S. Use of imitation process in creating interaction and learning behaviors; Development of methods for segmenting and classifying visual input to recognize human behavior; Validation of approach to humanoid motor control and imitation.