Mobile manipulators and humanoid robots should have the ability to use objects in their environments. Previous work has shown significant advantages to robots that can remove objects that interfere with their goal. We propose the next step. Just like the fictional character ‘MacGyver,’ robots should construct simple machines and tools from arbitrary objects. This video presents our progress in developing and validating ‘MacGyver’ skills in a simulated rescue mission.

We present a novel algorithm that solves the distributor's pallet packing problem. In contrast to existing algorithms, our method optimizes stack stability in addition to stack volume. Furthermore, our algorithm explicitly handles cases where the construction of homogeneous layers of packages with equal height is impossible due to differences in package heights and quantities. The algorithm is a nested beam search that separately optimizes local and global evaluation criteria. We show successful results on both real world and synthetic data sets, compare our performance to an existing algorithm and demonstrate experimental applications in simulation and on a real palletizing robot.