https://github.com/sustechgameai/text-to-building-in-minecraft
공식 코드3D Building Generation in Minecraft via Large Language Models
Papers with Code 아카이브
Trajectory Planning
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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/tbenciolini/safe-and-non-conservative-trajectory-planning
공식 코드https://github.com/ucla-mobility/AutoVLA
공식 코드https://github.com/udg-lai/modref2023
공식 코드https://github.com/unic-lab/qedgix
공식 코드GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network
https://github.com/wangy18/manifoldinterceptmethod
공식 코드https://github.com/wyddmw/WiseAD
공식 코드WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model
https://github.com/wzzheng/gpd
공식 코드https://github.com/yahiaetman/ms-level-gen
공식 코드https://github.com/zigned/nuplan_zigned
공식 코드Reinforced Imitative Trajectory Planning for Urban Automated Driving
https://github.com/zlatanajanovic/SBMP_PerfDriving
공식 코드Search-Based Task and Motion Planning for Hybrid Systems: Agile Autonomous Vehicles
https://gitlab.com/rei08/perception-energy-planner
공식 코드https://github.com/CeroChen/GraphBashedCoordination
https://github.com/Cognitive-AI-Systems/MAPF-GPT
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning
https://github.com/PathPlanning/Push-and-Rotate--CBS--PrioritizedPlanning
Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robots
https://github.com/SnDehghani/pcgrl_d_m
https://github.com/XGX-CURRY/uavSim
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach
https://github.com/Zhefan-Xu/trajectory_optimization
https://github.com/cmc623/Formation-control-with-lane-preference
https://github.com/cmc623/flexible-lane-direction-intersection
https://github.com/cmc623/formation-control-experiments
https://github.com/dixantmittal/mctsnet
https://github.com/drexubery/viewcrafter
ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis
https://github.com/eachsheep/shortcutsbench
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
https://github.com/fabiopardo/qmap
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks
https://github.com/glassices/sokoban_planner
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
https://github.com/kalebbennaveed/Trajectory-Planning-for-Autonomous-Vehicles-Using-HRL
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement Learning
https://github.com/kylevedder/Push-and-Rotate
Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robots
https://github.com/learningandplanningICLR/learningandplanning
https://github.com/poi233/pcgrl_rts
https://github.com/robin-karlsson0/dslp
Lane Graph Estimation for Scene Understanding in Urban Driving
https://github.com/smearle/gym-pcgrl
https://github.com/theilem/uavSim
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach
https://github.com/wangxiao5791509/DeepMTA_PyTorch
MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
https://github.com/wzzheng/doe
https://github.com/yangyucheng000/papercode-2/tree/main/WS-VAD-mindspore-main
VAD: Vectorized Scene Representation for Efficient Autonomous Driving
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.