Planning for Dynamic Nonprehensile Object Transport

Abstract

Generalized planning methods for dynamic manipulation struggle to efficiently solve kinodynamic constraints. Gradient-based methods suffer from initialization sensitivity, local optimum convergence, and lack of feasibility guarantees, while sampling-based methods can require large computation times if there exist challenging boundary conditions. Iterative Time Optimal Path Parameterization, or iTOPP, guarantees a feasible local minimum for a dynamic grasping problem by iteratively decreasing transit time for a trajectory initially generated to satisfy kinodynamic contact constraints. We demonstrate solutions that can handle initial or final goal states defined as quasistatically infeasible, in which purely quasistatic motions cannot generate a warm start trajectory. We also design an indirect adaptive controller that can track a desired dynamic grasping trajectory assuming unknown object mass and location parameters.