From 1f32bc0928bc2b70e913fafaae14fda547a6be11 Mon Sep 17 00:00:00 2001 From: Gustavo Moura <27751225+gustavo-moura@users.noreply.github.com> Date: Tue, 29 Oct 2024 13:43:46 -0300 Subject: [PATCH 1/2] Update third_party_environments.md Add Itomori description and links to repo --- 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..e161785cb 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 a Gymnasium environment for risk-aware UAV flight. Designed as part of a research project, Itomori 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). From 856a844359a6fab25cd7e37ce042b319c1c60198 Mon Sep 17 00:00:00 2001 From: Gustavo Moura <27751225+gustavo-moura@users.noreply.github.com> Date: Tue, 29 Oct 2024 19:01:52 -0300 Subject: [PATCH 2/2] Update third_party_environments.md --- docs/environments/third_party_environments.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/environments/third_party_environments.md b/docs/environments/third_party_environments.md index e161785cb..5f18877a6 100644 --- a/docs/environments/third_party_environments.md +++ b/docs/environments/third_party_environments.md @@ -224,7 +224,7 @@ goal-RL ([Gymnasium-Robotics](https://robotics.farama.org/)). ![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 a Gymnasium environment for risk-aware UAV flight. Designed as part of a research project, Itomori 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. + 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/)