Using surface and subsurface sensing, we have developed a perception system for autonomous retrieval of buried objects. The subsurface sensing system uses Ground Penetrating Radar (GPR) to detect and localize buried objects. An industrial robotic arm is used to position the GPR antenna, and a 2-D laser rangefinder system generates an elevation map which is used to guide the robotic arm. Using this setup we have automated the GPR data collection process. An image processing algorithm is used to locate the object of interest in the GPR data. After the object is located, we use sense and dig cycle to retrieve the object. During this loop the excavator alternately removes a layer of soil and takes a subsurface scan. The electromagnetic (EM) wave propagation velocity in the soil can be computed by comparing the data from the previous subsurface scan with the current one. With each successive iteration, the estimates of the object's size, shape, and location improve. This loop is repeated until the object is within certain distance and able to be retrieved. This "sense and dig cycle" enables the system to handle layered soil to some extent since at every cycle the EM propagation velocity estimate is updated. The computationally intensive parts of the processing are run in parallel on multiple processors to achieve near real-time performance. The system so far has been used to detect, locate and retrieve small buried objects in the testbed.


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