Prediction-based uncertainty estimation for adaptive crowd navigation

Kapil D. Katyal, Katie Popek, Gregory D. Hager, I. Jeng Wang, Chien Ming Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fast, collision-free motion through human environments remains a challenging problem for robotic systems. In these situations, the robot’s ability to reason about its future motion and other agents is often severely limited. By contrast, biological systems routinely make decisions by taking into consideration what might exist in the future based on prior experience. In this paper, we present an approach that provides robotic systems the ability to make future predictions of the environment. We evaluate several deep network architectures, including purely generative and adversarial models for map prediction. We further extend this approach to predict future pedestrian motion. We show that prediction plays a key role in enabling an adaptive, risk-sensitive control policy. Our algorithms are able to generate future maps with a structural similarity index metric up to 0.899 compared to the ground truth map. Further, our adaptive crowd navigation algorithm is able to reduce the number of collisions by 43% in the presence of novel pedestrian motion not seen during training.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in HCI - 1st International Conference, AI-HCI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
EditorsHelmut Degen, Lauren Reinerman-Jones
PublisherSpringer
Pages353-368
Number of pages16
ISBN (Print)9783030503338
DOIs
StatePublished - 2020
Event1st International Conference on Artificial Intelligence in HCI, AI-HCI 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020 - Copenhagen, Denmark
Duration: Jul 19 2020Jul 24 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12217 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Artificial Intelligence in HCI, AI-HCI 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
CountryDenmark
CityCopenhagen
Period7/19/207/24/20

Keywords

  • Adaptive crowd navigation
  • Human robot interaction
  • Prediction
  • Reinforcement learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Prediction-based uncertainty estimation for adaptive crowd navigation'. Together they form a unique fingerprint.

Cite this