Sept 21, 2011
Ask someone with her hands in her lap to pick up a coffee mug on the table she’s sitting at, and she’ll extract her hand from under the table and stretch her arm out toward the mug.
Instruct an autonomous robot to perform the same feat, and it may think for a few seconds, zigzag its robotic hand back and forth under the table, then perform what look kind of like calisthenics for a few seconds more before finally reaching for the mug.
As intuitive as it seems to a human being, spontaneously planning a trajectory around obstacles in free space is a monstrously complex computation. As a consequence, most motion-planning algorithms give up on the idea of finding the most efficient path between the robot’s initial state and its goal, settling for any path that won’t introduce collisions.
By combining two innovative algorithms developed at MIT, researchers in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Laboratory for Information and Decision Systems (LIDS) have built a new robotic motion-planning system that calculates much more efficient trajectories through free space. This month at the Institute of Electrical and Electronics Engineers’ (IEEE) International Conference on Intelligent Robots and Systems, they’ll present a paper that describes the application of the algorithm to a robotic arm.
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