# An intent-based approach for creating assistive robots' control systems

arXiv: https://arxiv.org/abs/2005.12106 · HTML: https://mlsanity.com/paper/2005.12106/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2020.

## Built on by (most cited first, 4 of 4)

- [A comparative analysis of deep learning models for lung segmentation on X-ray images](https://mlsanity.com/paper/2404.06455/) (2024)
- [Interpreting and learning voice commands with a Large Language Model for a robot system](https://mlsanity.com/paper/2407.21512/) (2024)
- [Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema](https://mlsanity.com/paper/2409.09677/) (2024)
- [Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks](https://mlsanity.com/paper/2410.00129/) (2024)

## Abstract (arXiv)

The current research standards in robotics demand general approaches to robots' controllers development. In the assistive robotics domain, the human-machine interaction plays a substantial role. Especially, the humans generate intents that affect robot control system. In the article an approach is presented for creating control systems for assistive robots, which reacts to users' intents delivered by voice commands, buttons, or an operator console. The whole approach was applied to the real system consisting of customised TIAGo robot and additional hardware components. The exemplary experiments performed on the platform illustrate the motivation for diversification of human-machine interfaces in assistive robots.