Impact-Aware Dual-Arm Manipulation

Abstract

This article presents an impact-aware manipulation framework for logistics, where growing e-commerce demands have increased the need for faster and more flexible package handling solutions. The proposed framework addresses swiftly grabbing and placing objects in depalletizing tasks with dual-arm robotic systems. Impact-aware robotics leverages intentional collisions to achieve dynamic interactions and has the potential to be faster and more energy efficient than classical quasi-static approaches. The generation of desired impacts brings multiple challenges encompassing robust motion generation, managing impacts with objects, enforcing hardware and safety constraints, contact state sensing, and simulation of contact behavior. To tackle these challenges, we developed within the EU-funded Impact-Aware Manipulation (I.AM.) project an integrated solution exploiting nonsmooth mechanics for impact modeling, dynamical systems for motion generation, QP-based control for constraint enforcement, internal state sensing without external force transducers, and batch-capable impact simulation. This article highlights the benefits of the proposed approach in terms of speed (a 29% decrease in average task time) and energy efficiency (a 35% decrease) through a systematic comparison between classical grabbing and impact-aware swift grabbing and tossing. In summary, our article underscores the transformative potential of impact-aware technologies in revolutionizing robotic logistics operations.