This paper presents a method to incorporate ergonomics into the optimization of action sequences for bi-manual human-robot cooperation tasks with continuous physical interaction. Our first contribution is a novel computational model of the human that allows prediction of an ergonomics assessment corresponding to each step in a task. The model is learned from human motion capture data in order to predict the human pose as realistically as possible. The second contribution is a combination of this prediction model with an informed graph search algorithm, which allows computation of human-robot cooperative plans with improved ergonomics according to the incorporated method for ergonomic assessment. The concepts have been evaluated in simulation and in a small user study in which the subjects manipulate a large object with a 32 DoF bimanual mobile robot as partner. For all subjects, the ergonomic-enhanced planner shows their reduced ergonomic cost compared to a baseline planner.

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This paper presents a system for cooperatively manipulating large objects between a human and a robot. This physical interaction system is designed to handle, transport, or manipulate large objects of different shapes in cooperation with a human. Unique points are the bi-manual physical cooperation, the sequential characteristic of the cooperation including contact changes, and a novel architecture combining force interaction cues, interactive search-based planning, and online trajectory and motion generation. The resulting system implements a mixed initiative collaboration strategy, deferring to the human when his intentions are unclear, and driving the task once understood. This results in an easy and intuitive human-robot interaction. It is evaluated in simulations and on a bi-manual mobile robot with 32 degrees of freedom.

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Virtual avatars have been employed in many contexts, from simple conversational agents to communicating the internal state and intentions of large robots when interacting with humans. Rarely, however, are they employed in scenarios which require non-verbal communication of spatial information or dynamic interaction from a variety of perspectives. When presented on a flat screen, many illusions and visual artifacts interfere with such applications, which leads to a strong preference for physically-actuated heads and faces. By adjusting the perspective projection used to render 3D avatars to match a viewer's physical perspective, they could provide a useful middle ground between typical 2D/3D avatar representations, which are often ambiguous in their spatial relationships, and physically-actuated heads/faces, which can be difficult to construct or impractical to use in some environments. A user study was conducted to determine to what extent a head-tracked perspective projection scheme was able to mitigate the issues in readability of a 3D avatar's expression or gaze target compared to use of a standard perspective projection. To the authors' knowledge, this is the first user study to perform such a comparison, and the results show not only an overall improvement in viewers' accuracy when attempting to follow the avatar's gaze, but a reduction in spatial biases in predictions made from oblique viewing angles@en