Probabilistic Algorithms in Robotics

Abstract

This article describes a methodology for programming robots known as probabilistic robotics. The probabilistic paradigm pays tribute to the inherent uncertainty in robot perception, relying on explicit representations of uncertainty when determining what to do. This article surveys some of the progress in the field, using in-depth examples to illustrate some of the nuts and bolts of the basic approach. Our central conjecture is that the probabilistic approach to robotics scales better to complex real-world applications than approaches that ignore a robot's uncertainty.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2000
Accession Number
ADA376946

Entities

People

  • Sebastian Thrun

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Autonomous Navigation
  • Autonomous Systems
  • Computational Science
  • Control Systems
  • Information Processing
  • Machine Learning
  • Motion Planning
  • Operations Research
  • Probabilistic Models
  • Probability
  • Reasoning
  • Robot Navigation
  • Robots
  • Sequential Monte Carlo Methods
  • Software Design
  • Three Dimensional

Fields of Study

  • Computer science

Readers

  • Military History of the United States in the 20th Century.
  • Robotics and Automation.
  • Statistical inference.

Technology Areas

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