Human-Robot Handovers using Task-Space Quadratic Programming

TL;DR

This paper introduces a task-space quadratic programming approach for human-robot handovers, effectively managing timing, pose constraints, and haptic exchange to enable seamless object transfer.

Contribution

It presents a novel formulation of handover as constraints within a task-space quadratic programming framework, improving synchronization and handling of pose constraints.

Findings

Successfully implemented on Panda robot for object transfer from humans.

Achieved implicit timing and trajectory encounters during handovers.

Enhanced coordination in human-robot object exchanges.

Abstract

Bidirectional object handover between a human and a robot enables an important functionality skill in robotic human-centered manufacturing or services. The problem in achieving this skill lies in the capacity of any solution to deal with three important aspects: (i) synchronized timing for the handing over phases; (ii) the handling of object pose constraints; and (iii) understanding the haptic exchanging to seamlessly achieve some steps of the (i). We propose a new approach for (i) and (ii) consisting in explicitly formulating the handover process as constraints in a task-space quadratic programming control framework to achieve implicit time and trajectory encounters. Our method is implemented on Panda robotic arm taking objects from a human operator.