Towards Super-Nominal Payload Handling: Inverse Dynamics Analysis for Multi-Skill Robotic Manipulation

TL;DR

This paper demonstrates that articulated robots like the Franka Emika Panda can handle payloads more than twice their rated capacity by analyzing inverse dynamics, expanding their operational envelope for complex manipulation tasks.

Contribution

It provides empirical evidence that traditional payload limits are conservative and introduces a framework for leveraging inverse dynamics to expand robot payload capabilities.

Findings

Robots can handle over twice their rated payloads.

Expanded operational envelope for payload handling.

Potential for combining non-prehensile and grasping motions.

Abstract

Motion planning for articulated robots has traditionally been governed by algorithms that operate within manufacturer-defined payload limits. Our empirical analysis of the Franka Emika Panda robot demonstrates that this approach unnecessarily restricts the robot's dynamically-reachable task space. These results establish an expanded operational envelope for such robots, showing that they can handle payloads of more than twice their rated capacity. Additionally, our preliminary findings indicate that integrating non-prehensile motion primitives with grasping-based manipulation has the potential to further increase the success rates of manipulation tasks involving payloads exceeding nominal limits.