From 1d353b31e80fa6672ac66fe1d1649a260651faa5 Mon Sep 17 00:00:00 2001
From: Gustavo Moura <27751225+gustavo-moura@users.noreply.github.com>
Date: Tue, 29 Oct 2024 19:50:42 -0300
Subject: [PATCH] Add Itomori custom env to third_party_environments.md (#1235)

---
 docs/environments/third_party_environments.md | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/docs/environments/third_party_environments.md b/docs/environments/third_party_environments.md
index 706065c82..5f18877a6 100644
--- a/docs/environments/third_party_environments.md
+++ b/docs/environments/third_party_environments.md
@@ -219,6 +219,13 @@ goal-RL ([Gymnasium-Robotics](https://robotics.farama.org/)).
 
   A simple environment using [PyBullet](https://github.com/bulletphysics/bullet3) to simulate the dynamics of a [Bitcraze Crazyflie 2.x](https://www.bitcraze.io/documentation/hardware/crazyflie_2_1/crazyflie_2_1-datasheet.pdf) nanoquadrotor.
 
+- [Itomori: UAV Risk-aware Flight Environment](https://github.com/gustavo-moura/itomori)
+
+  ![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.29.1-blue)
+  ![GitHub stars](https://img.shields.io/github/stars/gustavo-moura/itomori)
+
+  Itomori is an environment for risk-aware UAV flight, it provides tools to solve Chance-Constrained Markov Decision Processes (CCMDP). The env allows to simulate, visualize, and evaluate UAV navigation in complex and risky environments, incorporating variables like GPS uncertainty, collision risk, and adaptive flight planning. Itomori is intended to support UAV path-planning research by offering adjustable parameters, detailed visualizations, and insights into agent behavior in uncertain environments.
+
 - [OmniIsaacGymEnvs: Gym environments for NVIDIA Omniverse Isaac ](https://github.com/NVIDIA-Omniverse/OmniIsaacGymEnvs/)
 
   Reinforcement Learning Environments for [Omniverse Isaac simulator](https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html).