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Trajectory Planning

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하위 태스크: 1
평가표: 2
보존된 평가 기록: 7

Trajectory planning for industrial robots consists of moving the tool center point from point A to point B while avoiding body collisions over time. Trajectory planning is sometimes referred to as motion planning and erroneously as path planning. Trajectory planning is distinct from path planning in that it is parametrized by time. Essentially trajectory planning encompasses path planning in addition to planning how to move based on velocity, time, and kinematics.

코드

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

https://github.com/AbhijeetKrishnan/aml-for-player-modeling

공식 코드

Towards Action Model Learning for Player Modeling

https://github.com/CognitiveAISystems/Dynamic-Neural-Potential-Field

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Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving Obstacles

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/E2E-AD/AD-MLP

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Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

https://github.com/GAIGResearch/LearningFM

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Learning Local Forward Models on Unforgiving Games

https://github.com/Liang-ZX/SkillDiffuser

공식 코드

SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution

https://github.com/LorenzoFederici/RobustTrajectoryDesignbyRL

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Reinforcement Learning for Low-Thrust Trajectory Design of Interplanetary Missions

https://github.com/MandiZhao/robot-collab

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RoCo: Dialectic Multi-Robot Collaboration with Large Language Models

https://github.com/OpenPerceptionX/TCP

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Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline

https://github.com/ProSeCo-Planning/proseco_planning

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Parallelization of Monte Carlo Tree Search in Continuous Domains

https://github.com/ProSeCo-Planning/ros_proseco_planning/tree/main/python/proseco/inverse_reinforcement_learning

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Learning Reward Models for Cooperative Trajectory Planning with Inverse Reinforcement Learning and Monte Carlo Tree Search

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/adaptivesubgoalsearch/adaptive_subs

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Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search

https://github.com/alignmentresearch/learned-planner

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Planning in a recurrent neural network that plays Sokoban

https://github.com/alignmentresearch/train-learned-planner

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Planning in a recurrent neural network that plays Sokoban

https://github.com/alniyatrui/cafe-ad

공식 코드

CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving

https://github.com/amidos2006/gym-pcgrl

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Tree Search vs Optimization Approaches for Map Generation

https://github.com/amidos2006/marahel

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Multi-Objective level generator generation with Marahel

https://github.com/andrewcropper/iggp

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Inductive general game playing

https://github.com/andrewcropper/mlj19-iggp

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Inductive general game playing

https://github.com/chaytonmin/OFF-Net

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ORFD: A Dataset and Benchmark for Off-Road Freespace Detection

https://github.com/chaytonmin/Off-Road-Freespace-Detection

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ORFD: A Dataset and Benchmark for Off-Road Freespace Detection

https://github.com/cirrick/multi_uav_data_harvesting

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Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks

https://github.com/clear-nus/ltldog

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LTLDoG: Satisfying Temporally-Extended Symbolic Constraints for Safe Diffusion-based Planning

https://github.com/deepmind/boxoban-levels

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Single-Agent Policy Tree Search With Guarantees

https://github.com/deepmind/deepmind-research/tree/master/physics_planning_games

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Physically Embedded Planning Problems: New Challenges for Reinforcement Learning

https://github.com/deepmind/levintreesearch_cm

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Levin Tree Search with Context Models

https://github.com/devaansh100/a_star

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A Training Data Recipe to Accelerate A* Search with Language Models

https://github.com/dixantmittal/expose

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ExPoSe: Combining State-Based Exploration with Gradient-Based Online Search

https://github.com/dvij542/offtersim

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WROOM: An Autonomous Driving Approach for Off-Road Navigation

https://github.com/eslam211/conservative-and-distributional-marl

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Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning

https://github.com/exomag/finite-sample-uncertainty-planning-automatica

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Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety Guarantees

https://github.com/facebookresearch/searchformer

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Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

https://github.com/fiorina1212/attention-buckets

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Fortify the Shortest Stave in Attention: Enhancing Context Awareness of Large Language Models for Effective Tool Use

https://github.com/gabe-yhlee/immp-public

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MMP++: Motion Manifold Primitives with Parametric Curve Models

https://github.com/google-deepmind/levintreesearch_cm

공식 코드

Levin Tree Search with Context Models

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