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Motion Planning

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<span style="color:grey; opacity: 0.6">( Image credit: Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://git.uwaterloo.ca/a9sarkar/traffic_behavior_modeling

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Solution Concepts in Hierarchical Games under Bounded Rationality with Applications to Autonomous Driving

https://github.com/AAIR-lab/AAIR-JEDAI

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JEDAI: A System for Skill-Aligned Explainable Robot Planning

https://github.com/AlexS28/SABER

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SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots

https://github.com/Amir-Samadi/VVF-TP

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A Novel Deep Neural Network for Trajectory Prediction in Automated Vehicles Using Velocity Vector Field

https://github.com/ApolloAuto/apollo

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Baidu Apollo EM Motion Planner

https://github.com/BoyuanChen/visual-selfmodeling

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Full-Body Visual Self-Modeling of Robot Morphologies

https://github.com/DriveVLA/OpenDriveVLA

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OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model

https://github.com/Ezharjan/AutoSceneGen

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Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner

https://github.com/GTLIDAR/safe-nav-locomotion

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Integrated Task and Motion Planning for Safe Legged Navigation in Partially Observable Environments

https://github.com/GeorgeDu/vision-based-robotic-grasping

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Vision-based Robotic Grasping From Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review

https://github.com/Hu-Hanyang/MARAG

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Multi-Agent Reach-Avoid Games: Two Attackers Versus One Defender and Mixed Integer Programming

https://github.com/IRVLUTD/SceneReplica

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SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes

https://github.com/IrisLi17/bridge_construction

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Learning Design and Construction with Varying-Sized Materials via Prioritized Memory Resets

https://github.com/KafuuChikai/Dashing-for-the-Golden-Snitch-Multi-Drone-RL

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Dashing for the Golden Snitch: Multi-Drone Time-Optimal Motion Planning with Multi-Agent Reinforcement Learning

https://github.com/KavrakiLab/pyre

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Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions

https://github.com/MPC-Berkeley/hmpc_raidnet

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Scalable Multi-modal Model Predictive Control via Duality-based Interaction Predictions

https://github.com/Mahmoud-Selim/Safe-Reinforcement-Learning-for-Black-Box-Systems-Using-Reachability-Analysis

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Safe Reinforcement Learning Using Black-Box Reachability Analysis

https://github.com/MajidMoghadam2006/RL-frenet-trajectory-planning-in-CARLA

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An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet Space

https://github.com/MartinBraquet/vector-field-obstacle-avoidance

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Vector Field-based Collision Avoidance for Moving Obstacles with Time-Varying Elliptical Shape

https://github.com/NVIDIA-Omniverse/Orbit

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Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments

https://github.com/NVlabs/UnseenObjectClustering

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Predicting Stable Configurations for Semantic Placement of Novel Objects

https://github.com/Pearl-UTexas/POMDP-HD

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Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics

https://github.com/SS47816/AGI-Elo

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AGI-Elo: How Far Are We From Mastering A Task?

https://github.com/Shuijing725/CrowdNav_DSRNN

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Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning

https://github.com/Shuijing725/CrowdNav_Prediction_AttnGraph

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Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

https://github.com/StanfordASL/LearnedSamplingDistributions

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Learning Sampling Distributions for Robot Motion Planning

https://github.com/StanfordASL/MATS

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MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control

https://github.com/StanfordASL/mantrap

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Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot Interactions

https://github.com/StanfordVL/JRMOT_ROS

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JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset

https://github.com/TheCamusean/grasp_diffusion

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SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

https://github.com/Tim-Salzmann/l4casadi

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Neural Potential Field for Obstacle-Aware Local Motion Planning

https://github.com/Tinker-Twins/MARL-Simulator

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Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement Learning

https://github.com/Tsinghua-Space-Robot-Learning-Group/SpaceRobotEnv

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A Learning System for Motion Planning of Free-Float Dual-Arm Space Manipulator towards Non-Cooperative Object

https://github.com/UVA-BezzoRobotics-AMRLab/cbf_tracking

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Soft Actor-Critic-based Control Barrier Adaptation for Robust Autonomous Navigation in Unknown Environments

https://github.com/VishnuDuttSharma/deep-multirobot-task

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Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection

https://github.com/Woodenonez/DyObAv_MPCnEBM_Warehouse

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Future-Oriented Navigation: Dynamic Obstacle Avoidance with One-Shot Energy-Based Multimodal Motion Prediction

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.