Automatic Mapping of Dynamic Office Environments

Authors:
Clayton Kunz;Thomas Willeke;Illah R. Nourbakhsh
Affiliations:
Mobot, Inc., Pittsburgh, PA;Mobot, Inc., Pittsburgh, PA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA
Venue:
Autonomous Robots
Year:
1999

Citing 4
Cited 1

Real-time obstacle avoidance for manipulators and mobile robots

International Journal of Robotics Research
Default reasoning about spatial occupancy

Artificial Intelligence
Probabilistic robot navigation in partially observable environments

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Challenge problems for artificial intelligence

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2

Symbolic Place Recognition in Voronoi-Based Maps by Using Hidden Markov Models

Journal of Intelligent and Robotic Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a robot, InductoBeast, that greets a new office building by learning the floorplan automatically, with minimal human intervention and a priori knowledge. Our robot architecture is unique because it combines aspects of both abductive and inductive mapping methods to solve this problem. We present experimental results spanning three ofiice environments, mapped and navigated during normal business hours. We hope these results help to establish a performance benchmark against which robust and adaptive mapping robots of the future may be measured.