> For the complete documentation index, see [llms.txt](https://roborus.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://roborus.gitbook.io/whitepaper/use-cases/7.1-simulation-based-tasks.md).

# 7.1 Simulation-Based Tasks

Before transitioning into physical deployments, Roborus leverages **simulation environments** to validate its privacy-first, proof-based task model. Simulation offers a safe, scalable, and low-cost entry point for both developers and clients.

#### **Path Planning**

Robotic agents simulate navigation tasks, finding the most efficient routes in a given environment. This is crucial for logistics robots, drones, and autonomous vehicles.

* **Value**: Clients can test delivery or patrol strategies before real-world deployment.
* **Benefit**: Robots gain reputation through provable completions in a risk-free setting.

#### **Coverage Mapping**

Agents simulate tasks like cleaning, surveillance, or inspection, where complete area coverage is required.

* **Value**: Industries such as warehouse logistics or agriculture benefit from optimized coverage strategies.
* **Benefit**: Robots demonstrate real-world capabilities without physical constraints.

#### **Vision Labeling**

Simulated agents assist with computer vision by labeling or verifying datasets.

* **Value**: Supports AI development for robotics perception systems.
* **Benefit**: Provides decentralized workforce for one of the most resource-intensive AI tasks.