# CostNav: A Navigation Benchmark for Real-World Economic-Cost Evaluation of Physical AI Agents

arXiv: https://arxiv.org/abs/2511.20216 · HTML: https://mlsanity.com/paper/2511.20216/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 71 references that are in the map.
- First posted on arXiv 25 Nov 2025.

## Builds on (most cited first, 25 of 25)

- [SWE-bench: Can Language Models Resolve Real-World GitHub Issues?](https://mlsanity.com/paper/2310.06770/) (2023)
- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [WebArena: A Realistic Web Environment for Building Autonomous Agents](https://mlsanity.com/paper/2307.13854/) (2023)
- [AgentBench: Evaluating LLMs as Agents](https://mlsanity.com/paper/2308.03688/) (2023)
- [Habitat: A Platform for Embodied AI Research](https://mlsanity.com/paper/1904.01201/) (2019)
- [GAIA: a benchmark for General AI Assistants](https://mlsanity.com/paper/2311.12983/) (2023)
- [AI2-THOR: An Interactive 3D Environment for Visual AI](https://mlsanity.com/paper/1712.05474/) (2017)
- [FAST: Efficient Action Tokenization for Vision-Language-Action Models](https://mlsanity.com/paper/2501.09747/) (2025)
- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration](https://mlsanity.com/paper/2310.07896/) (2023)
- [ViNT: A Foundation Model for Visual Navigation](https://mlsanity.com/paper/2306.14846/) (2023)
- [GNM: A General Navigation Model to Drive Any Robot](https://mlsanity.com/paper/2210.03370/) (2022)
- [SWE-Lancer: Can Frontier LLMs Earn 1 Million from Real-World Freelance Software Engineering?](https://mlsanity.com/paper/2502.12115/) (2025)
- [The Marathon 2: A Navigation System](https://mlsanity.com/paper/2003.00368/) (2020)
- [NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance](https://mlsanity.com/paper/2505.08712/) (2025)
- [UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI](https://mlsanity.com/paper/2412.20977/) (2024)
- [Towards Autonomous Micromobility through Scalable Urban Simulation](https://mlsanity.com/paper/2505.00690/) (2025)
- [Review of Autonomous Mobile Robots for the Warehouse Environment](https://mlsanity.com/paper/2406.08333/) (2024)
- [Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation](https://mlsanity.com/paper/2409.12471/) (2024)
- [OpenBench: A New Benchmark and Baseline for Semantic Navigation in Smart Logistics](https://mlsanity.com/paper/2502.09238/) (2025)
- [Conv1D Energy-Aware Path Planner for Mobile Robots in Unstructured Environments](https://mlsanity.com/paper/2104.01560/) (2021)
- [Energy-aware Multi-UAV Coverage Mission Planning with Optimal Speed of Flight](https://mlsanity.com/paper/2402.10529/) (2024)
- [CANVAS: Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction](https://mlsanity.com/paper/2410.01273/) (2024)
- [Energy-efficient Path Planning for Ground Robots by Combining Air and Ground Measurements](https://mlsanity.com/paper/1907.06337/) (2019)
- [Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering](https://mlsanity.com/paper/2504.14135/) (2025)

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

- [MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation in Urban Environments](https://mlsanity.com/paper/2512.22867/) (2025)
- [Towards Trustworthy Physical Intelligence: From Theory to Practice Across Life Cycle](https://mlsanity.com/paper/2607.22877/) (2026)

## Abstract (arXiv)

Current navigation benchmarks focus on task success but do not capture the economic constraints essential for commercializing autonomous delivery systems. We introduce CostNav, an Economic Navigation Benchmark that evaluates physical AI agents on a cost-revenue and break-even analysis, pairing Isaac Sim's collision and cargo dynamics with industry-standard data such as Securities and Exchange Commission (SEC) filings and Abbreviated Injury Scale (AIS) injury reports. To our knowledge, CostNav is the first physics-grounded economic benchmark to use regulatory and financial data to quantify the gap between navigation metrics and commercial deployment, revealing that high task-success rates alone do not ensure economic viability. Evaluating seven baselines (two rule-based and five imitation-learning methods), we find no method economically viable: all yield negative contribution margins. CANVAS, using only an RGB camera and GPS, attains the highest task success and the least-negative margin among methods with non-zero Service-Level Agreement (SLA) compliance (-28.40/run), outperforming LiDAR-equipped Nav2 w/ GPS (-37.34/run). A sim-trained policy evaluated on a real delivery robot yields SLA compliance close to its simulation result, indicating that policy performance in CostNav's simulation transfers to real-world deployment. We challenge the community to achieve economic viability on CostNav, which scores methods by cost-revenue outcomes. All resources are available at https://github.com/worv-ai/CostNav.