mr-d-self-driving Goto Github PK

crazyflie_ros

ROS Driver for Bitcraze Crazyflie

crazyswarm

A Large Quadcopter Swarm

cs454-final-project

cube-f411re-chibios

Integrating ChibiOS to STMCubeMX on Nucle-F411RE

cvg_quadrotor_swarm

We present a cost-effective framework for the prototyping of vision-based quadrotor multi-robot systems, which core characteristics are: modularity, compatibility with different platforms and being flight-proven. The framework is fully operative, which works in simulation and in real flight tests of up to 5 drones, and was demonstrated with the participation in the 2013 International Micro Air Vehicle Indoor Flight Competition (Toulouse, France).

cvrp

This repository contains algorithms in C++ to solve the Capacitated Vehicle Routing Problem (cvrp).

cvrptw_milp

Solving a Capacitated Vehicle Routing Problem with time windows constraints (CVRPTW) with Mixed Integer Linear Programming (MILP) in python-gurobi API.

cyber-rt

Redistributed Apollo CyberRT, built with CMake.

cyber_cmake

cyberrt-x86

将Apollo cyberRT移植到docker外面

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

daqp

A dual active-set algorithm for convex quadratic programming

dash

Real-time motion planner and autonomous vehicle simulator in the browser, built with WebGL and Three.js.

data-driven-control

A reliable controller is critical for execution of safe and smooth maneuvers of an autonomous vehicle. The controller must be robust to external disturbances, such as road surface, weather, wind conditions, and so on. It also needs to deal with internal variations of vehicle sub-systems, including powertrain inefficiency, measurement errors, time delay, etc. These factors introduce issues in controller performance. In this paper, a feed-forward compensator is designed via a data-driven method to model and optimize the controller’s performance. Principal Component Analysis (PCA) is applied for extracting influential features, after which a Time Delay Neural Network is adopted to predict control errors over a future time horizon. Based on the predicted error, a feedforward compensator is then designed to improve control performance. Simulation results in different scenarios show that, with the help of with the proposed feedforward compensator, the maximum path tracking error and the steering wheel angle oscillation are improved by 44.4% and 26.7%, respectively.

datadrivenmpc

Model predictive control based on data-driven model

datampc_parking

arXiv 2011.00413: (MATLAB Simulation) Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach.

db-cbs

decision_making

decision_making_2022

Decision-making method based on reinforcement-learning-based branching

decisionplanning

Contingency Model Predictive Control for Linear Time-Varying Systems; Interaction-Aware Game-Theoretic Motion Planning for Automated Vehicles using Bi-level Optimization

deep-lcc

DeeP-LCC for mixed traffic

deep-tesla

End-to-End Learning from Human and Autopilot Driving

deepdrive

Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving

deepplanning

YIPSO, A Novel Autonomous Parking System

delta_prediction

ROS package for Delta Autonomy's Prediction Pipeline

demo_board

Simple setup of the demo board

deployed_vehicle_code

despot

The DESPOT online POMDP solver

dftpav

A lightweight differential flatness-based trajectory planner for car-like robots