In this letter, we propose an efficient and highly versatile loco-manipulation planning for humanoid robots. Locomanipulation planning is a key technological brick enabling humanoid robots to autonomously perform object transportation by manipulating them. We formulate planning of the alternation and sequencing of footsteps and grasps as a graph search problem with a new transition model that allows for a flexible representation of loco-manipulation. Our transition model is quickly evaluated by relocating and switching the reachability maps depending on the motion of both the robot and object. We evaluate our approach by applying it to loco-manipulation usecases, such as a bobbin rolling operation with regrasping, where the motion is automatically planned by our framework.
In order to achieve robots' working around humans, safe contacts against objects, humans, and environments with broad area of their body should be allowed. Furthermore, it is desirable to actively use those contacts for achieving tasks. Considering that, many practical applications will be realized by whole-body close interaction of many contacts with others. Therefore, robots are strongly expected to achieve whole-body interaction behavior with objects around them. Recently, it becomes possible to construct whole-body tactile sensor network by the advancement of research for tactile sensing system. Using such tactile sensors, some research groups have developed robots with whole-body tactile sensing exterior. However, their basic strategy is making a distributed 1-axis tactile sensor network covered with soft thin material. Those are not sufficient for achieving close interaction and detecting complicated contact changes. Therefore, we propose “Soft Sensor Flesh.” Basic idea of “Soft Sensor Flesh” is constructing robots' exterior with soft and thick foam with many sensor elements including multiaxis tactile sensors. In this paper, a constructing method for the robot systems with such soft sensor flesh is argued. Also, we develop some prototypes of soft sensor flesh and verify the feasibility of the proposed idea by actual behavior experiments.
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