Chatting about Conditional Trajectory Prediction
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 compl...
| Authors | Yuxiang Zhao, Wei Huang, Haipeng Zeng et al. |
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| Primary category | cs.RO |
| Published | 20 April 2026 |
| Last updated at source | 20 April 2026 |
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