Program synthesis by examples for object repositioning tasks

We address the problem of synthesizing human-readable computer programs for robotic object repositioning tasks based on human demonstrations. A stack-based domain specific language (DSL) is introduced for object repositioning tasks, and a learning algorithm is proposed to synthesize a program in this DSL based on human demonstrations. Once the synthesized program has been learned, it can be rapidly verified and refined in the simulator via further demonstrations if necessary, then finally executed on an actual robot to accomplish the corresponding learned tasks in the physical world. By performing demonstrations on a novel tablet interface, the time required for teaching is greatly reduced compared with using a real robot. Experiments show a variety of object repositioning tasks such as sorting, kitting, and packaging can be programmed using this approach.