# To Lead or to Follow? Adaptive Robot Task Planning in Human-Robot Collaboration

arXiv: https://arxiv.org/abs/2401.01483 · HTML: https://mlsanity.com/paper/2401.01483/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jan 2024.

## Built on by (most cited first, 1 of 1)

- [From Where to How: Continuous 4D Interaction Forecasting from Egocentric Video](https://mlsanity.com/paper/2609.08636/) (2026)

## Abstract (arXiv)

Adaptive task planning is fundamental to ensuring effective and seamless human-robot collaboration. This paper introduces a robot task planning framework that takes into account both human leading/following preferences and performance, specifically focusing on task allocation and scheduling in collaborative settings. We present a proactive task allocation approach with three primary objectives: enhancing team performance, incorporating human preferences, and upholding a positive human perception of the robot and the collaborative experience. Through a user study, involving an autonomous mobile manipulator robot working alongside participants in a collaborative scenario, we confirm that the task planning framework successfully attains all three intended goals, thereby contributing to the advancement of adaptive task planning in human-robot collaboration. This paper mainly focuses on the first two objectives, and we discuss the third objective, participants' perception of the robot, tasks, and collaboration in a companion paper.