mlsanityData to 13 Oct 2026

Chatting about Conditional Trajectory Prediction

arXiv 2604.18126 ↗First posted 20 Apr 2026cs.RO cs.CVcited by 0

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Abstract (arXiv)

Human behavior has the nature of mutual dependencies, which requires human-robot interactive systems to predict surrounding agents trajectories by modeling complex social interactions, avoiding collisions and executing safe path planning. While there exist many trajectory prediction methods, most of them do not incorporate the own motion of the ego agent and only model interactions based on static information. We are inspired by the humans theory of mind during trajectory selection and propose a Cross time domain intention-interactive method for conditional Trajectory prediction(CiT). Our proposed CiT conducts joint analysis of behavior intentions over time, and achieves information complementarity and integration across different time domains. The intention in its own time domain can be corrected by the social interaction information from the other time domain to obtain a more precise intention representation. In addition, CiT is designed to closely integrate with robotic motion planning and control modules, capable of generating a set of optional trajectory prediction results for all surrounding agents based on potential motions of the ego agent. Extensive experiments demonstrate that the proposed CiT significantly outperforms the existing methods, achieving state-of-the-art performance in the benchmarks.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 20 Apr 2026.

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21 of 38 references.

References · 21

  1. 2018Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networkscited by 688
  2. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 530
  3. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 418
  4. 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
  5. 2018Convolutional Social Pooling for Vehicle Trajectory Predictioncited by 221
  6. 2022Stochastic Trajectory Prediction via Motion Indeterminacy Diffusioncited by 185
  7. 2019Multi-Agent Tensor Fusion for Contextual Trajectory Predictioncited by 131
  8. 2023Leapfrog Diffusion Model for Stochastic Trajectory Predictioncited by 130
  9. 2019Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecastingcited by 87
  10. 2022M2I: From Factored Marginal Trajectory Prediction to Interactive Predictioncited by 81
  11. 2020PiP: Planning-informed Trajectory Prediction for Autonomous Drivingcited by 80
  12. 2022ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planningcited by 63
9 more
  1. 2022MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Predictioncited by 59
  2. 2023LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraintscited by 51
  3. 2022End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Mapscited by 22
  4. 2021Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidancecited by 21
  5. 2021Deep Structured Reactive Planningcited by 18
  6. 2024Diffusion-Based Environment-Aware Trajectory Predictioncited by 14
  7. 2024C2F-TP: A Coarse-to-Fine Denoising Framework for Uncertainty-Aware Trajectory Predictioncited by 9
  8. 2021TIP: Task-Informed Motion Prediction for Intelligent Vehiclescited by 8
  9. 2024Robot Trajectron: Trajectory Prediction-based Shared Control for Robot Manipulationcited by 7

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