Brain-computer-interface based automatic control of robo-rat using a-star

Abstract

Robots have been applied to the tasks which are not appropriate for human; for examples dangerous, tough, dirty tasks or the tasks which require high accuracy, good repeatability, quick motion. Nowadays, rescue robots are applied to explore unknown areas or even to rescue victims after disasters because of their several superior performances over human. An operator controls every single motion of the rescue robot remotely using information from onboard sensors and cameras. However, in an extreme situation after disaster where the area is messy with many broken objects and obstacles, area exploration and victim rescue are very difficult and time consuming. This situation requires a rescuer who at least can make simple decision and execute the actions. Robo-rat fits very well with this situation. Robo-rat is a rat whose brain is implanted by electrodes and trained to follow commands in the form of brain stimulation using electrical square-wave signals. Three commands are trained to Robo-rat; go straight, turn left and turn right. The electrode at Medial Forebrain Bundle (MFB) is stimulated for go straight command. The electrode at left Somatosensory Cortex is stimulated for turn left command. The electrode at right Somatosensory Cortex is stimulated for turn right command. After manual control of Robo-rat, automatic control is implemented using A-star optimization technique. A camera takes the top view image of the maze. Image processing is conducted to identify Robo-rat position. Based on the map of the maze and the current position, A-star is used to determine the shortest path to the goal position. A PC determines and stimulates electrical pulses at the proper electrodes automatically. The experimental results reveal the feasibility of using Robo-rat for rescue purpose.