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Humanoid Multimodal Tactile-Sensing Modules

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2 Author(s)
Mittendorfer, P. ; Inst. for Cognitive Syst., Tech. Univ. Munchen, Munich, Germany ; Cheng, G.

In this paper, we present a new generation of active tactile modules (i.e., HEX-O-SKIN), which are developed in order to approach multimodal whole-body-touch sensation for humanoid robots. To better perform like humans, humanoid robots need the variety of different sensory modalities in order to interact with their environment. This calls for certain robustness and fault tolerance as well as an intelligent solution to connect the different sensory modalities to the robot. Each HEX-O-SKIN is a small hexagonal printed circuit board equipped with multiple discrete sensors for temperature, acceleration, and proximity. With these sensors, we emulate the human sense of temperature, vibration, and light touch. Off-the-shelf sensors were utilized to speed up our development cycle; however, in general, we can easily extend our design with new discrete sensors, thereby making it flexible for further exploration. A local controller on each HEX-O-SKIN preprocesses the sensor signals and actively routes data through a network of modules toward the closest PC connection. Local processing decreases the necessary network and high-level processing bandwidth, while a local analog-to-digital conversion and digital-data transfers are less sensitive to electromagnetic interference. With an active data-routing scheme, it is also possible to reroute the data around broken connections-yielding robustness throughout the global structure while minimizing wirings. To support our approach, multiple HEX-O-SKIN are embedded into a rapid-prototyped elastomer skin material and redundantly connected to neighboring modules by just four ports. The wiring complexity is shifted to each HEX-O-SKIN such that a power and data connection between two modules is reduced to four noncrossing wires. Thus, only a very simple robot-specific base frame is needed to support and wire the HEX-O-SKIN to a robot. The potential of our multimodal sensor modules is demonstrated experimentally on a robot platform.

Published in:

Robotics, IEEE Transactions on  (Volume:27 ,  Issue: 3 )

Date of Publication:

June 2011

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