ActivePusher: Active Learning and Planning with Residual Physics for Nonprehensile Manipulation
Planning with learned dynamics models offers a promising approach toward versatile real-world manipulation, particularly in nonprehensile settings such as pushing or rolling, where accurate analytical models are difficult to obtain. However, collecting training data for learning-based methods can be…