A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Abstract

The overall goal of this work is to develop the perception, estimation, planning, and control techniques necessary to enable autonomous agents to perform robustly and intelligently in complex uncertain domains. This includes the ability to intelligently interact and coordinate with humans or other agents so as to achieve goals effectively and efficiently.Specifically our goal has been to develop algorithms for effective and efficient planning in domains that are characterized by a variety of action types, each with continuous parameters, for example the variety of manipulation actions available to a robot (picking, placing, pushing, tilting, etc.). Furthermore, the actions take place in the presence of uncertainty both as to the current state of the world and as to the actual result of the action.

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Document Details

Document Type
Technical Report
Publication Date
Dec 05, 2017
Accession Number
AD1051486

Entities

People

  • Leslie P. Kaelbling

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autonomous Navigation
  • Autonomous Systems
  • Data Science
  • Gaussian Processes
  • Geometry
  • Information Science
  • Monte Carlo Method
  • Motion Planning
  • Multitarget Tracking
  • Navigation
  • Probability
  • Robotics
  • Robots
  • Statistical Algorithms
  • Unmanned Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers