Update readme (#71)

# Pull Request

### What change is being made

Update readme.

### Why this change is being made

N//A

### Tested

N/A

GitOrigin-RevId: 89fb7c1ea4406965f26f53d8c87f50798ae00fc8

Author: dbellicoso-bdai

CITATION.cff

@@ -0,0 +1,11 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+- family-names: "Bellicoso"
+  given-names: "Dario"
+- family-names: "Wollschläger"
+  given-names: "Annika"
+title: "Exploy: EXport and dePLOY Reinforcement Learning policies"
+date-released: 2026-03-11
+version: 0.1.0
+url: "https://github.com/bdaiinstitute/exploy"

README.md

@@ -4,7 +4,7 @@ EXport and dePLOY Reinforcement Learning policies.
 
 The core idea lies in a "self-contained" export approach:
 Rather than exporting only the neural network policy, this tool captures the entire environment
-logic—including observation generation and action processing—into a single ONNX file.
+logic, including observation generation and action processing, into a single ONNX file.
 By tracing Torch operations from the simulation environment, the exporter embeds the computational
 layers required to transform raw robot state interfaces into policy inputs and policy outputs into
 executable commands.
@@ -13,6 +13,8 @@ By encapsulating the environment's computation graph within the model file itsel
 this library minimizes operational effort and maximizes confidence that a policy will behave
 identically in simulation and on physical hardware.
 
+Authors: Dario Bellicoso, Annika Wollschläger
+
 ## Features
 
 - **Environment Exporting**: Export RL environments and policies from
@@ -25,7 +27,7 @@ identically in simulation and on physical hardware.
 ## Project Structure
 
 - `control/`: C++ controller library with ONNX Runtime integration
-- `exporter/`: Python exporter package for policy and environment export
+- `exploy/`: Python exporter package for policy and environment export
 - `examples/`: Usage examples for supported frameworks
 - `docs/`: Documentation source files
 
@@ -83,6 +85,9 @@ pixi run export-isaaclab
 import exploy.exporter.core as exporter
 from exploy.exporter.frameworks.isaaclab.env import IsaacLabExportableEnvironment
 
+# Create an environment.
+env = . . .
+
 # Create an exportable environment from a ManagerBasedRLEnv
 exportable_env = IsaacLabExportableEnvironment(env)
 
@@ -269,3 +274,18 @@ This project is licensed under the MIT License - see the [LICENSE](LICENSE)
 file for details.
 
 Copyright (c) 2026 Robotics and AI Institute LLC dba RAI Institute
+
+## Citation
+
+If you use this work in your research or project, please consider citing it using the 'Cite this repository'
+button in the sidebar, or using:
+
+```bibtex
+@misc{exploy2026,
+  author = {Dario Bellicoso, Annika Wollschläger},
+  title = {Exploy: EXport and dePLOY Reinforcement Learning policies},
+  month = {March},
+  year = {2026},
+  url = {https://github.com/bdaiinstitute/exploy}
+}
+```