Planning Impact-Driven Logistic Tasks

Abstract

This letter proposes a decoupled two-level model-based planning strategy and control for a class of robotic tasks involving impact to be made with desired performance and constraints. The first part solves the problem of planning a robotic arm trajectory from a given state (position and velocity) to another desired one, enabling non-stop trajectory cycles. The second part is an impact-aware model-based plugin; it is specific to each task and links the desired task-space impact objective to a via-point in the joint-space. The two parts are then combined to achieve the entire task. Our approach is assessed with real-robot experiments demonstrating how this strategy can be used to perform tossing, grabbing, and boxing or any combination of them in sorting logistics-industry use-cases.