Community for applying LLMs to robotics and a robot simulator with ChatGPT integration
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Updated
Jan 20, 2024 - Python
Community for applying LLMs to robotics and a robot simulator with ChatGPT integration
Drone Racing @ NeurIPS 2019, built on Microsoft AirSim
Programmable Engine for Drone Reinforcement Learning Applications
🔥 Synthetic and real-world 2d/3d dataset for semantic and instance segmentation (BMVC 2022 Oral)
Autonomous UAV Navigation without Collision using Visual Information in Airsim
A multi-modal, photo-realistic dataset for online end-to-end scene change detection and more (accepted to IROS2021).
Combines JSBSim and Airsim with a python module to simulate a fixedwing
Python code for Deep Reinforcement Learning with Transfer Learning in a Simulated Environment
Simulator + benchmark suite for Micro Aerial Vehicle design.
Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments
Visuomotor policies from event-based cameras through representation learning and reinforcement learning. Accompanies our paper: https://arxiv.org/abs/2103.00806
Autonomous Drone for Object Tracking
Deep Reinforcement Learning based autonomous navigation for quadcopters using PPO algorithm.
Master's thesis about autonomous navigation of a drone in indoor environments carried out to obtain the degree of Master of Science in Computer Science Engineering (University of Liège, academic year 2020-2021).
Deep Reinforcement Learning based autonomous navigation in realistic simulation environments.
This code is the result of the collaboration of RL Turkey team.
A Novelty Approach to Emulate Field Data Captured by Unmanned Aerial Vehicles for Training Deep Learning Algorithms Used for Search-and-Rescue Activities at Sea
鸿钧:一个基于虚幻引擎和 AirSim 的仿真系统,让用户以简单轻松的配置方式搭建定制化的无人机作战环境。 本项目是鸿钧的 python 控制器,其通过 Socket 协议与由基于虚幻引擎和 AirSim 的仿真系统——鸿钧建立通讯,并控制其中仿真的无人机,进行飞行和战斗任务。用户可以使用 Python 语言编写无人机的飞行任务程序,完成无人机的编队飞行、攻击战斗、集群对抗等任务。 本团队在 AirSim 的基础上拓展出了攻击、战斗系统,可以对无人机的作战环境进行模拟,本项目可作为集群智能的训练平台,适用于无人机集群对抗、轰炸敌方目标单位等任务的人工智能训练。 该项目已被清华大学猛狮无人驾驶实验室和南京航空航天大学无人机实验室的研究生团队采用,并于人工智能仿真训练,并发表相关科研论文
Using DDPG and ConvLSTM to control a drone to avoid obstacle in AirSim
A hover system for Microsoft AirSim using reinforcement learning (Q-learning and SARSA)
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