In collaboration with the Humanoid robotics and Computational science department (HRCN) at the Advanced Telecommunication Research Institute (ATR), it implemented the PDA-based language learning game in DB, an anthropomorphic hydraulic robot with 30 DOFs. The robot learns the names of two boxes and directions of movements (left and right). Once the robot has correctly learned the words, it can be pushed the boxes in a desired direction upon verbal command.
We try to place a table in front of the robot, with two boxes of different colors on it (e/g/ green and pink, to facilitate color tracking). An external stereo vision system tracks the boxes position.
DB is mounted at the pelvis. It is 1.85 meters tall, weighs 80 kg, and is driven by 25 linear hydraulic actuators and 5 rotary hydraulic actuators. Each arm has 7DOFs. The vision system consists of 2 cameras fixed on the ceiling and facing the robot. A color blobs tracking system generates blob position information at 60 Hz. In the application, the vision module of DB robot extracts relevant changes in the boxes position and direction of displacement.
Similarly to what was done with Robota. Speech and vision inputs are associated in an ANN, computed on board of the PDA. During retrieval, the output neurons activate absolute goal positions, and relative sequences of movement, such that the robot can push the requested box in the requested direction. The communication from PDA to robot is still assured by RS232 serial interface in the experiment, because the aim of the experiment was to evaluate the use of the PDA as a remote control. Wireless capabilities of the iPAQ will be used in further experiments.
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