Corpus ID: 221655800

Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction

@article{Nishimura2020RiskSensitiveSA,
  title={Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction},
  author={Haruki Nishimura and B. Ivanovic and Adrien Gaidon and M. Pavone and M. Schwager},
  journal={ArXiv},
  year={2020},
  volume={abs/2009.05702}
}
  • Haruki Nishimura, B. Ivanovic, +2 authors M. Schwager
  • Published 2020
  • Computer Science, Engineering
  • ArXiv
  • This paper presents a novel online framework for safe crowd-robot interaction based on risk-sensitive stochastic optimal control, wherein the risk is modeled by the entropic risk measure. The sampling-based model predictive control relies on mode insertion gradient optimization for this risk measure as well as Trajectron++, a state-of-the-art generative model that produces multimodal probabilistic trajectory forecasts for multiple interacting agents. Our modular approach decouples the crowd… CONTINUE READING
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    References

    SHOWING 1-10 OF 39 REFERENCES
    Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction
    • 70
    • PDF
    Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data.
    • 17
    • PDF
    Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
    • Michael Everett, Y. Chen, J. How
    • Computer Science, Engineering
    • 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    • 2018
    • 106
    • PDF
    The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
    • B. Ivanovic, M. Pavone
    • Computer Science
    • 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
    • 2019
    • 59
    • PDF
    Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning
    • 47
    • PDF
    Risk-Sensitive Optimal Feedback Control for Haptic Assistance
    • 68
    • PDF
    Deep Local Trajectory Replanning and Control for Robot Navigation
    • 12
    • PDF
    Real-Time Stochastic Optimal Control for Multi-Agent Quadrotor Systems
    • 25
    • PDF
    SACBP: Belief Space Planning for Continuous-Time Dynamical Systems via Stochastic Sequential Action Control
    • 6
    • Highly Influential
    • PDF
    Chance-Constrained Optimal Path Planning With Obstacles
    • 159
    • PDF