# Bearing Rigidity Theory and its Applications for Control and Estimation of Network Systems: Life Beyond Distance Rigidity

arXiv: https://arxiv.org/abs/1803.05505 · HTML: https://mlsanity.com/paper/1803.05505/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Mar 2018.

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

- [LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation](https://mlsanity.com/paper/2506.01538/) (2025)
- [GenSwarm: Scalable Multi-Robot Code-Policy Generation and Deployment via Language Models](https://mlsanity.com/paper/2503.23875/) (2025)

## Abstract (arXiv)

The problem of distributed control and estimation for multi-agent systems with limited sensing capabilities is a practical challenge motivated by incomplete and imperfect sensing. This article addresses an important case where each agent in a network can only sense the relative bearings to their nearest neighbors. The study of this topic is motivated mainly by the rapid development of bearing-only sensors such as optical cameras or sensor arrays. This article provides a tutorial review on this topic focusing on the problems of formation control and network localization. A key component of this review is a presentation of the recently developed bearing rigidity theory, which defines a necessary architectural feature of multi-agent systems aiming to solve these two problems. This article presents a high-level summary of recently developed algorithms solving these problems, various simulation examples, and discussions pointing to the relevant literature and important remaining challenges in this area.