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activityforecasting_python

Python implementation of Activity Forecasting (Kitani et al. 2012).

air

algorithms

automated-driving-control

automatic-driving-decision-and-planning-for-matlab

automatic_ticket_purchase

大麦网抢票脚本

awesome-self-driving-car

An awesome list of self-driving cars

bolero

Behavior Optimization and Learning for Robots

cadrl

Implementation of paper "Decentralized Non-communicating Multiagent Collision Avoidance with Deep Reinforcement Learning". NO LONGER MAINTAINED. CHECK OUT CrowdNav.

cadrl_ros

ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

carla_trajectory_controller

carlo

2D Driving Simulator

carnd-path-planning-project

Self-Driving Car Engineer Program: Path Planning Project

context-pomdp

cplusplusthings

C++那些事

cpprobotics

cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control

crazyflie_human

ROS wrapper for pedestrian prediction.

dataset-api

The ApolloScape Open Dataset for Autonomous Driving and its Application.

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

deeprl

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

densetnt

desire

DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents

dig-into-apollo

Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.

drivelm

DriveLM: Driving with Graph Visual Question Answering

driving-irl-ngsim

(T-ITS) Driving Behavior Modeling using Naturalistic Human Driving Data with Inverse Reinforcement Learning

dwa-rl

Novel reinforcement learning based local planner that accounts for the dynamic constraints of the robot to enable smooth robot trajectories. Reward shaping is done to enable a spatially aware navigation.

epsilon

faster

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

gerona

GeRoNa (Generic Robot Navigation) is a modular robot navigation framework, that bundles path planning and path following (including obstacle detection) and manages communication between the individual modules. It is designed to be easily extensible for new tasks and robot models.