LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval
2013
As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment)
Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and
Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle
(UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For
LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect)
filter based on object shape features with a color-histogram-based object detector. Our vision system was able to
learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based
on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement
autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies – including
outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not
integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and
behavior capabilities that may be applied to future autonomous robot systems.
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