# Toward Adaptive Cooperation: Model-Based Shared Control Using LQ-Differential Games

arXiv: https://arxiv.org/abs/2403.11146 · HTML: https://mlsanity.com/paper/2403.11146/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Mar 2024.

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

- [A Reinforcement Learning Framework for Safety-Aware Haptic Shared Control in Surgical Robotics](https://mlsanity.com/paper/2610.15422/) (2026)

## Abstract (arXiv)

This paper introduces a novel model-based adaptive shared control to allow for the identification and design challenge for shared-control systems, in which humans and automation share control tasks. The main challenge is the adaptive behavior of the human in such shared control interactions. Consequently, merely identifying human behavior without considering automation is insufficient and often leads to inadequate automation design. Therefore, this paper proposes a novel solution involving online identification of the human and the adaptation of shared control using Linear-Quadratic differential games. The effectiveness of the proposed online adaptation is analyzed in simulations and compared with a non-adaptive shared control from the state of the art. Finally, the proposed approach is tested through human-in-the-loop experiments, highlighting its suitability for real-time applications.