# Exploration-RRT: A multi-objective Path Planning and Exploration Framework for Unknown and Unstructured Environments

arXiv: https://arxiv.org/abs/2104.03724 · HTML: https://mlsanity.com/paper/2104.03724/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2021.

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

- [STAGE: Scalable and Traversability-Aware Graph based Exploration Planner for Dynamically Varying Environments](https://mlsanity.com/paper/2402.02566/) (2024)
- [Information Gain Is Not All You Need](https://mlsanity.com/paper/2504.01980/) (2025)
- [VANDERER: Map-Free Exploration using Future-Aware and Visual-Curiosity-Guided Diffusion Policy](https://mlsanity.com/paper/2606.14879/) (2026)
- [SGE: Semantically-Guided Exploration for Unstructured Environments via Image-Space Waypoint Sampling](https://mlsanity.com/paper/2608.29315/) (2026)

## Abstract (arXiv)

This article establishes the Exploration-RRT algorithm: A novel general-purpose combined exploration and pathplanning algorithm, based on a multi-goal Rapidly-Exploring Random Trees (RRT) framework. Exploration-RRT (ERRT) has been specifically designed for utilization in 3D exploration missions, with partially or completely unknown and unstructured environments. The novel proposed ERRT is based on a multi-objective optimization framework and it is able to take under consideration the potential information gain, the distance travelled, and the actuation costs, along trajectories to pseudo-random goals, generated from considering the on-board sensor model and the non-linear model of the utilized platform. In this article, the algorithmic pipeline of the ERRT will be established and the overall applicability and efficiency of the proposed scheme will be presented on an application with an Unmanned Aerial Vehicle (UAV) model, equipped with a 3D lidar, in a simulated operating environment, with the goal of exploring a completely unknown area as efficiently and quickly as possible