Human motion trajectory prediction: a survey

ARAndrey RudenkoLPLuigi PalmieriMHMichael HermanKMKris M KitaniDMDariu M Gavrila

Örebro University · Robert Bosch (Germany) · +2 more institutions

Indexed inarxivcrossref

Abstract

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots, and advanced surveillance systems. This article provides a survey of human motion trajectory prediction. We review, analyze, and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing…

Citation impact

610
total citations
FWCI
36.98
Percentile
100%
References
233
Citations per year

Authors

6
  • AR
    Andrey RudenkoCorresponding

    Örebro University, Robert Bosch (Germany)

  • LP
    Luigi Palmieri

    Robert Bosch (Germany)

  • MH
    Michael Herman
  • KM
    Kris M Kitani

    Carnegie Mellon University

  • DM
    Dariu M Gavrila

    Delft University of Technology

Topics & keywords

Keywords
  • Trajectory
  • Human motion
  • Motion (physics)
  • Key (lock)
  • Work (physics)
  • Motion planning
  • Selection (genetic algorithm)
No related works found for this paper.

Funding