Example for AUAV 2022 with obstacle avoidance.

Overview

AUAV 2022 Sample

This is a sample PX4 based quadrotor path planning framework based on Ubuntu 20.04 and ROS noetic for the IEEE Autonomous UAS 2022 competition.

You will need to install xterm and the standard PX4/gazebo requirements.

sudo apt install xterm

Build the catkin workspace.

pip3 install pymavlink --user
mkidr ~/catkin
cd ~/catkin
mkdir src
cd src
git clone https://github.com/jgoppert/auav_2022_sample.git
git submodule update --init --recursive
catkin build

Run the simulation for each trial.

Note: To fly PX4 you will need to have QGroundControl running and manually arm it and put it in offboard mode. For the competition we do not want your scirpts to do this automatically. For testing and in simulation, you can have a script that manually arms the drone and puts it in offboard mode.

We are following this safety procedure so that the pilot will have the only authority to arm the drone and switch the mode to offboard from the RC transmitter.

cd ~/catkin
. ./devel/setup.bash
roslaunch auav_2022_sample sim.launch world:=worlds/trial_1.world 
roslaunch auav_2022_sample sim.launch world:=worlds/trial_2.world 
roslaunch auav_2022_sample sim.launch world:=worlds/trial_3.world 
roslaunch auav_2022_sample sim.launch world:=worlds/trial_4.world 

Please adapt your code to work with this framework, we expect to launch each drone with the command:

roslaunch auav_2022_sample live.launch

Path Planning

Two examples of path planning libraries are included that use the depth camera information:

  • PX4 avoidance: Uses VFH3D+ approach, simple approach, not very robust
  • path planning: Uses octomap and OMPL library for (RRT), could be improved to use Quadrotor dynamics
Owner
James Goppert
James Goppert
Hand Gesture Volume Control is AIML based project which uses image processing to control the volume of your Computer.

Hand Gesture Volume Control Modules There are basically three modules Handtracking Program Handtracking Module Volume Control Program Handtracking Pro

VITTAL 1 Jan 12, 2022
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation

LightNet++ !!!New Repo.!!! ⇒ EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights !!

linksense 237 Jan 05, 2023
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

Denys Rozumnyi 139 Dec 26, 2022
Object Depth via Motion and Detection Dataset

ODMD Dataset ODMD is the first dataset for learning Object Depth via Motion and Detection. ODMD training data are configurable and extensible, with ea

Brent Griffin 172 Dec 21, 2022
A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding

Business Problem A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maxim

Kübra Bilinmiş 1 Jan 15, 2022
Cross Quality LFW: A database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments

Cross-Quality Labeled Faces in the Wild (XQLFW) Here, we release the database, evaluation protocol and code for the following paper: Cross Quality LFW

Martin Knoche 10 Dec 12, 2022
Integrated physics-based and ligand-based modeling.

ComBind ComBind integrates data-driven modeling and physics-based docking for improved binding pose prediction and binding affinity prediction. Given

Dror Lab 44 Oct 26, 2022
Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation

CorrNet This project provides the code and results for 'Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation'

Gongyang Li 13 Nov 03, 2022
Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"

OANet implementation Pytorch implementation of OANet for ICCV'19 paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network", by

Jiahui Zhang 225 Dec 05, 2022
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.

IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver

IDRL 105 Dec 17, 2022
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C

F-G Fernandez 1.2k Dec 29, 2022
PyTorch implementation of DeepDream algorithm

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

121 Nov 05, 2022
Hyper-parameter optimization for sklearn

hyperopt-sklearn Hyperopt-sklearn is Hyperopt-based model selection among machine learning algorithms in scikit-learn. See how to use hyperopt-sklearn

1.4k Jan 01, 2023
DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene.

DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene. We achieve NeRF-comparable novel-view synthesis quality with super-fast convergence.

sunset 709 Dec 31, 2022
Simple tutorials using Google's TensorFlow Framework

TensorFlow-Tutorials Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano Tutorial

Nathan Lintz 6k Jan 06, 2023
Code for BMVC2021 paper "Boundary Guided Context Aggregation for Semantic Segmentation"

Boundary-Guided-Context-Aggregation Boundary Guided Context Aggregation for Semantic Segmentation Haoxiang Ma, Hongyu Yang, Di Huang In BMVC'2021 Pape

Haoxiang Ma 31 Jan 08, 2023
Efficiently Disentangle Causal Representations

Efficiently Disentangle Causal Representations Install dependency pip install -r requirements.txt Main experiments Causality direction prediction cd

4 Apr 01, 2022
Implementation of ECCV20 paper: the devil is in classification: a simple framework for long-tail object detection and instance segmentation

Implementation of our ECCV 2020 paper The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation This repo contains code o

twang 98 Sep 17, 2022