# PathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithms

arXiv: https://arxiv.org/abs/2105.01777 · HTML: https://mlsanity.com/paper/2105.01777/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 51 references that are in the map.
- First posted on arXiv 4 May 2021.

## Builds on (most cited first, 16 of 16)

- [Semantic Scene Completion from a Single Depth Image](https://mlsanity.com/paper/1611.08974/) (2016)
- [Cognitive Mapping and Planning for Visual Navigation](https://mlsanity.com/paper/1702.03920/) (2017)
- [Value Iteration Networks](https://mlsanity.com/paper/1602.02867/) (2016)
- [Motion Planning Networks](https://mlsanity.com/paper/1806.05767/) (2018)
- [Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners](https://mlsanity.com/paper/1907.06013/) (2019)
- [Gated Path Planning Networks](https://mlsanity.com/paper/1806.06408/) (2018)
- [Universal Planning Networks](https://mlsanity.com/paper/1804.00645/) (2018)
- [HouseExpo: A Large-scale 2D Indoor Layout Dataset for Learning-based Algorithms on Mobile Robots](https://mlsanity.com/paper/1903.09845/) (2019)
- [Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation](https://mlsanity.com/paper/1904.11102/) (2019)
- [Deeply Informed Neural Sampling for Robot Motion Planning](https://mlsanity.com/paper/1809.10252/) (2018)
- [Neural Manipulation Planning on Constraint Manifolds](https://mlsanity.com/paper/2008.03787/) (2020)
- [An Extensible Benchmarking Infrastructure for Motion Planning Algorithms](https://mlsanity.com/paper/1412.6673/) (2014)
- [Using Local Experiences for Global Motion Planning](https://mlsanity.com/paper/1903.08693/) (2019)
- [Path Planning in Support of Smart Mobility Applications using Generative Adversarial Networks](https://mlsanity.com/paper/1804.08396/) (2018)
- [Waypoint Planning Networks](https://mlsanity.com/paper/2105.00312/) (2021)
- [PathGAN: Local Path Planning with Attentive Generative Adversarial Networks](https://mlsanity.com/paper/2007.03877/) (2020)

## Built on by (most cited first, 6 of 6)

- [LLM-First Search: Self-Guided Exploration of the Solution Space](https://mlsanity.com/paper/2506.05213/) (2025)
- [ROS-X-Habitat: Bridging the ROS Ecosystem with Embodied AI](https://mlsanity.com/paper/2109.07703/) (2021)
- [Pareto Frontier Approximation Network (PA-Net) to Solve Bi-objective TSP](https://mlsanity.com/paper/2203.01298/) (2022)
- [Systematic Comparison of Path Planning Algorithms using PathBench](https://mlsanity.com/paper/2203.03092/) (2022)
- [Dynamic Q-planning for Online UAV Path Planning in Unknown and Complex Environments](https://mlsanity.com/paper/2402.06297/) (2024)
- [Hybrid DQN-TD3 Reinforcement Learning for Autonomous Navigation in Dynamic Environments](https://mlsanity.com/paper/2510.26646/) (2025)

## Abstract (arXiv)

Path planning is a key component in mobile robotics. A wide range of path planning algorithms exist, but few attempts have been made to benchmark the algorithms holistically or unify their interface. Moreover, with the recent advances in deep neural networks, there is an urgent need to facilitate the development and benchmarking of such learning-based planning algorithms. This paper presents PathBench, a platform for developing, visualizing, training, testing, and benchmarking of existing and future, classical and learned 2D and 3D path planning algorithms, while offering support for Robot Oper-ating System (ROS). Many existing path planning algorithms are supported; e.g. A*, wavefront, rapidly-exploring random tree, value iteration networks, gated path planning networks; and integrating new algorithms is easy and clearly specified. We demonstrate the benchmarking capability of PathBench by comparing implemented classical and learned algorithms for metrics, such as path length, success rate, computational time and path deviation. These evaluations are done on built-in PathBench maps and external path planning environments from video games and real world databases. PathBench is open source.