Ascending Stairway Modeling: A First Step Toward Autonomous Multi-Floor Exploration

Abstract

Many robotics platforms are capable of ascending stairways, but all existing approaches for autonomous stair climbing use stairway detection as a trigger for immediate traversal. In the broader context of autonomous exploration the ability to travel between floors of a building should be compatible with path planning, such that the robot can traverse a stairway at a time that is appropriate to its navigation goals. No system yet presented is capable of both localizing stairways on a map and estimating their properties, functions that in combination would enable stairways to be considered as traversable terrain in a path planning algorithm. We propose a method for modeling stairways as objects and localizing them on a map such that they can be subsequently traversed if they are of dimensions that the robotic platform is capable of climbing. Our system consists of two parts: a computationally efficient detector that leverages geometric cues from depth imagery to detect sets of ascending stairs, and a stairway modeler that uses multiple detections to infer the location and parameters of a stairway that is discovered during exploration. This video demonstrates the performance of the system in a number of real-world situations, modeling and localizing a variety of stairway types in both indoor and outdoor environments.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2012
Accession Number
ADA567543

Entities

People

  • David Baran
  • Jason J. Corso
  • Jeffrey A. Delmerico
  • Julian Ryde
  • Philip David

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Climbing
  • Detection
  • Detectors
  • Dihedral Angle
  • Environment
  • Information Operations
  • Mathematics
  • Military Research
  • Motion Planning
  • Point Clouds
  • Robots

Readers

  • Computer Vision.
  • Medical Imaging.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy