# Robot Trajectory Adaptation to Optimise the Trade-off between Human Cognitive Ergonomics and Workplace Productivity in Collaborative Tasks

arXiv: https://arxiv.org/abs/2207.03739 · HTML: https://mlsanity.com/paper/2207.03739/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2022.

## Built on by (most cited first, 2 of 2)

- [A Unified Architecture for Dynamic Role Allocation and Collaborative Task Planning in Mixed Human-Robot Teams](https://mlsanity.com/paper/2301.08038/) (2023)
- [ContactRL: Safe Reinforcement Learning based Motion Planning for Contact based Human Robot Collaboration](https://mlsanity.com/paper/2512.03707/) (2025)

## Abstract (arXiv)

In hybrid industrial environments, workers' comfort and positive perception of safety are essential requirements for successful acceptance and usage of collaborative robots. This paper proposes a novel human-robot interaction framework in which the robot behaviour is adapted online according to the operator's cognitive workload and stress. The method exploits the generation of B-spline trajectories in the joint space and formulation of a multi-objective optimisation problem to online adjust the total execution time and smoothness of the robot trajectories. The former ensures human efficiency and productivity of the workplace, while the latter contributes to safeguarding the user's comfort and cognitive ergonomics. The performance of the proposed framework was evaluated in a typical industrial task. Results demonstrated its capability to enhance the productivity of the human-robot dyad while mitigating the cognitive workload induced in the worker.