An adaptive hierarchical approach to lidar-based autonomous robotic navigation

Alexander J.W. Brooks, Wolfgang Fink, Mark A. Tarbell

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

2 Scopus citations

Abstract

Planetary missions are typically confined to navigationally safe environments, leaving areas of interest in rugged and/or hazardous terrain largely unexplored. Identifying and avoiding possible hazards requires dedicated path planning and limits the effectiveness of (semi-)autonomous systems. An adaptable, fully autonomous design is ideal for investigating more dangerous routes, increasing robotic exploratory capabilities, and improving overall mission efficiency from a science return perspective. We introduce hierarchical Lidar-based behavior motifs encompassing actions, such as velocity control, obstacle avoidance, deepest path navigation/exploration, and ratio constraint, etc., which can be combined and prioritized to form more complex behaviors, such as free roaming, object tracking, etc., as a robust framework for designing autonomous exploratory systems. Moreover, we introduce a dynamic Lidar environment visualization tool. Developing foundational behaviors as fundamental motifs (1) clarifies response priority in complex situations, and (2) streamlines the creation of new behavioral models by building a highly generalizable core for basic navigational autonomy. Implementation details for creating new prototypes of complex behavior patterns on top of behavior motifs are shown as a proof of concept for earthly applications. This paper emphasizes the need for autonomous navigation capabilities in the context of space exploration as well as the exploration of other extreme or hazardous environments, and demonstrates the benefits of constructing more complex behaviors from reusable standalone motifs. It also discusses the integration of behavioral motifs into multi-Tiered mission architectures, such as Tier-Scalable Reconnaissance.

Original languageEnglish (US)
Title of host publicationMicro- and Nanotechnology Sensors, Systems, and Applications X
EditorsM. Saif Islam, Thomas George, Achyut K. Dutta
PublisherSPIE
ISBN (Electronic)9781510617896
DOIs
StatePublished - Jan 1 2018
Event2018 Micro- and Nanotechnology (MNT) Sensors, Systems, and Applications X Conference - Orlando, United States
Duration: Apr 15 2018Apr 19 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10639
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other2018 Micro- and Nanotechnology (MNT) Sensors, Systems, and Applications X Conference
CountryUnited States
CityOrlando
Period4/15/184/19/18

Keywords

  • 2D Lidar data
  • Autonomous CISR systems
  • Deepest path navigation
  • Multi-Tiered robotic exploration architectures
  • Navigational behavior motifs
  • Obstacle avoidance
  • Ratio constraint
  • Velocity control

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Brooks, A. J. W., Fink, W., & Tarbell, M. A. (2018). An adaptive hierarchical approach to lidar-based autonomous robotic navigation. In M. S. Islam, T. George, & A. K. Dutta (Eds.), Micro- and Nanotechnology Sensors, Systems, and Applications X [106391X] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10639). SPIE. https://doi.org/10.1117/12.2303770