Impact-Aware Bimanual Catching of Large-Momentum Objects

TL;DR

An online optimization framework to estimate and predict the linear and angular motion of the object, search and select the optimal contact locations across every surface of the object to mitigate impact and realise the impact-aware catching motion on the compliant robotic system based on indirect force controller is proposed.

Abstract

This paper investigates one of the most challenging tasks in dynamic manipulation -- catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with its surrounding environment. Yet, the inevitable motion mismatch between the fast moving object and the approaching robot will result in large impulsive forces, which lead to the unstable contacts and irreversible damage to both the object and the robot. To address the above problems, we propose an online optimization framework to: 1) estimate and predict the linear and angular motion of the object; 2) search and select the optimal contact locations across every surface of the object to mitigate impact through sequential quadratic programming (SQP); 3) simultaneously optimize the end-effector motion, stiffness, and contact force for both robots using multi-mode trajectory optimization (MMTO); and 4) realise the impact-aware catching motion on the compliant robotic system based on indirect force controller. We validate the impulse distribution, contact selection, and impact-aware MMTO algorithms in simulation and demonstrate the benefits of the proposed framework in real-world experiments including catching large-momentum moving objects with well-defined motion, constrained motion and free-flying motion.

Figures (19)

• Figure 1: Two KUKA-iiwa robots catching a flying large-momentum box that weighs $4.2kg$ and travels with speed larger than 3.5ms.
• Figure 2: Step-by-step pictorial description of catching a tumbling-flying object.
• Figure 3: Overview of the proposed system. The experimental setup is in the center. The flow of information starts from the motion capture and results into the input of the robots. Solid arrows denote information transmission between modules and dotted lines denote functional dependency between components.
• Figure 4: Projection of contact velocity and force along normal and tangential directions (1) and 2D illustration for contact selection (2-3).
• Figure 5: Correspondence between Newton's restitution model for impacts and the mass-spring-damper system.

Theorems & Definitions (4)

• Remark 1
• Remark 2
• Remark 3
• Remark 4