Trajectory Representation Learning

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Overview

It studies how to encode paths—such as vehicle movement, robot actions, and agent interaction traces—so useful structure survives compression and supports downstream tasks. Common approaches include self-supervised contrastive and masked-sequence pretraining, graph and hierarchical encoders, spatial tokenization, and continuous latent or generative models for waypoints, motion phases, and trajectory-level effects. These representations are tested on similarity search, classification, travel-time prediction, driving forecasts, and robot manipulation or navigation across tasks and embodiments. A central tension is balancing compact, reusable embeddings with enough temporal, geometric, and contextual detail for reliable long-horizon prediction and control in new scenes or at different execution rates.

Latest papers

CardsList

48 papers12 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. Transition Information Density: Morphological Trajectories, Synesthetic Perception, and Structured Interpolation in Neural Training (or: The Synesthetic AI)

    Jul 3, 2026Sam MaoNeural Representation GeometryTrajectory Representation Learning

    New York University | Interactive Media Arts

  2. BIT-Nav: Brain-Inspired Trajectory Memory for Embodied Navigation

    Jun 19, 2026Rithvik Jonna, Aakash Gurram, Man Namgung +2Vision-Language ModelsEmbodied Navigation

    Department of Electrical and Computer Engineering Johns Hopkins University · Laboratory for Computational Sensing and Robotics Johns Hopkins University · DEVCOM Army Research Laboratory

  3. The Terminal Representation in Reinforcement Learning

    May 29, 2026Amir Esterhuysen, Anders JonssonRepresentation Learning for RLTrajectory Representation Learning

    Dept. Information and Communication Technologies Universitat Pompeu Fabra Barcelona, Spain

  4. TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning

    May 19, 2026Zhen Xiong, Shang-Ling Hsu, Cyrus ShahabiGeospatial Representation LearningTrajectory Representation Learning

    University of Southern California

  5. Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry

    May 14, 2026Zuyuan Zhang, Carlee Joe-Wong, Tian LanReinforcement LearningTrajectory Representation Learning

    The George Washington University · Carnegie Mellon University

  6. TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations

    May 7, 2026Maria Despoina Siampou, Gengchen Mai, Ni Lao +4Geospatial Foundation ModelsCross-Modal Alignment

    Google Research, Mountain View, CA · Dept. of Computer Science, University of Southern California, Los Angeles, CA · SEAI Lab, Dept. of Geography and the Environment, The University of Texas at Austin, Austin, TX +1

  7. Improving Molecular Force Fields with Minimal Temporal Information

    Apr 14, 2026Ali Mollahosseini, Mohammed Haroon Dupty, Wee Sun LeeMachine Learning Interatomic PotentialsTrajectory Representation Learning

    School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran · School of Computing, National University of Singapore, Singapore

  8. Hierarchical Spatial-Temporal Graph-Enhanced Model for Map-Matching

    Mar 25, 2026Anjun Gao, Zhenglin Wan, Pingfu Chao +1Spatiotemporal GNNsTrajectory Representation Learning

    School of Computer Science and Technology, Soochow University, Suzhou, China · Metasequoia Intelligence, Shenzhen, China · Department of Astronomy, The Ohio State University, Columbus, OH 43202 USA

  9. What Matters for Scalable and Robust Learning in End-to-End Driving Planners?

    Mar 16, 2026David Holtz, Niklas Hanselmann, Simon Doll +2End-to-End Autonomous DrivingAutonomous Driving Planning

    Mercedes-Benz AG · Max-Planck-Institute for Informatics, SIC

  10. Temporal Straightening for Latent Planning

    Mar 12, 2026Ying Wang, Oumayma Bounou, Gaoyue Zhou +4Latent-Space PlanningWorld Model-Based Planning

    New York University · Brown University · University of Toronto

  11. 3PoinTr: From Human Videos to Robot Policies with 3D Point-Track Plans

    Mar 9, 2026Adam Hung, Bardienus Pieter Duisterhof, Jeffrey IchnowskiHuman-to-Robot Motion ImitationRobot Policy Learning

    Carnegie Mellon University

  12. AutoTraces: Autoregressive Trajectory Forecasting via Multimodal Large Language Models

    Mar 9, 2026Teng Wang, Yanting Lu, Ruize WangRobot Motion PredictionTrajectory Prediction

  13. Context-Enriched Natural Language Descriptions of Vessel Trajectories

    Mar 8, 2026Kostas Patroumpas, Alexandros Troupiotis-Kapeliaris, Giannis Spiliopoulos +4Maritime TransportationTrajectory Representation Learning

    Archimedes/Athena RC, Greece · University of the Aegean, Greece · Athena RC, Greece +1

  14. Structural Action Transformer for 3D Dexterous Manipulation

    Mar 4, 2026Xiaohan Lei, Min Wang, Bohong Weng +2Robotic ManipulationRobot Imitation Learning

    MoE Key Laboratory of Brain-inspired Intelligent Perception and Cognition, University of Science and Technology of China · Institute of Artificial Intelligence, Hefei Comprehensive National Science Center

  15. TopoCurate:Modeling Interaction Topology for Tool-Use Agent Training

    Mar 2, 2026Jinluan Yang, Yuxin Liu, Zhengyu Chen +7LLM Agent TrainingRL for Tool Use

    Zhejiang University, Hangzhou, China · Meituan, Beijing, China.

  16. Towards Robot Skill Learning and Adaptation with Gaussian Processes

    Mar 2, 2026A K M Nadimul Haque, Fouad Sukkar, Sheila Sutjipto +3Robot Skill LearningRobot Learning

  17. Capturing Context-Aware Route Choice Semantics for Trajectory Representation Learning

    Oct 16, 2025Ji Cao, Yu Wang, Tongya Zheng +6Geospatial Representation LearningTrajectory Representation Learning

    College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China · Zhejiang Lab, Hangzhou 311121, China · Zhejiang Provincial Engineering Research Center for Real-Time SmartTech in Urban Security Governance, Hangzhou City University, Hangzhou 310015, China +2

  18. HiT-JEPA: A Hierarchical Self-supervised Trajectory Embedding Framework for Similarity Computation

    Jun 17, 2025Lihuan Li, Hao Xue, Shuang Ao +2Intelligent Transportation SystemsHierarchical Representation Learning

    University of New South Wales Sydney, Australia · Hong Kong University of Science and Technology (Guangzhou) Guangzhou, China