# Distributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents

arXiv: https://arxiv.org/abs/2304.08932 · HTML: https://mlsanity.com/paper/2304.08932/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Apr 2023.

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

- [VLM-RRT: Vision Language Model Guided RRT Search for Autonomous UAV Navigation](https://mlsanity.com/paper/2505.23267/) (2025)

## Abstract (arXiv)

In this work, a novel distributed search-planning framework is proposed, where a dynamically varying team of autonomous agents cooperate in order to search multiple objects of interest in three-dimension (3-D). It is assumed that the agents can enter and exit the mission space at any point in time, and as a result the number of agents that actively participate in the mission varies over time. The proposed distributed search-planning framework takes into account the agent dynamical and sensing model, and the dynamically varying number of agents, and utilizes model predictive control (MPC) to generate cooperative search trajectories over a finite rolling planning horizon. This enables the agents to adapt their decisions on-line while considering the plans of their peers, maximizing their search planning performance, and reducing the duplication of work.