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AI Reasoning Methods for Robotics

  • Michael Beetz
  • Raja Chatila
  • Joachim Hertzberg
  • Federico Pecora

Abstract

Artificial intelligence (AI ) reasoning technology involving, e. g., inference, planning, and learning, has a track record with a healthy number of successful applications. So can it be used as a toolbox of methods for autonomous mobile robots? Not necessarily, as reasoning on a mobile robot about its dynamic, partially known environment may differ substantially from that in knowledge-based pure software systems, where most of the named successes have been registered. Moreover, recent knowledge about the robot’s environment cannot be given a priori, but needs to be updated from sensor data, involving challenging problems of symbol grounding and knowledge base change.

This chapter sketches the main robotics-relevant topics of symbol-based AI reasoning. Basic methods of knowledge representation and inference are described in general, covering both logic- and probability-based approaches. The chapter first gives a motivation by example, to what extent symbolic reasoning has the potential of helping robots perform in the first place. Then (Sect. 14.2), we sketch the landscape of representation languages available for the endeavor. After that (Sect. 14.3), we present approaches and results for several types of practical, robotics-related reasoning tasks, with an emphasis on temporal and spatial reasoning. Plan-based robot control is described in some more detail in Sect. 14.4. Section 14.5 concludes.

Keywords

Bayesian Network Description Logic Constraint Satisfaction Problem Plan Execution Temporal Reasoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
2-D

two-dimensional

AAAI

Association for the Advancement of Artificial Intelligence

AI

artificial intelligence

BN

Bayesian network

CDC

cardinal direction calculus

CSP

constraint satisfaction problem

DBN

dynamic Bayesian network

DC

disconnected

DL

description logic

DPLL

Davis–Putnam algorithm

ECAI

European Conference on Artificial Intelligence

EC

externally connected

FF

fast forward

FOPL

first-order predicate logic

HTN

hierarchical task network

IA

interval algebra

ICAPS

International Conference on Automated Planning and Scheduling

IJCAI

International Joint Conference on Artificial Intelligence

IPC

international AI planning competition

KR

knowledge representation

LTL

linear temporal logic

MDP

Markov decision process

NTPP

nontangential proper part

OUR-K

ontology based unified robot knowledge

OWL

web ontology language

PA

point algebra

PI

policy iteration

POMDP

partially observable Markov decision process

PO

partially overlapping

POP

partial-order planning

PRM

probabilistic roadmap

RA

rectangle algebra

RCC

region connection calculus

SAT

International Conference on Theory and Applications of Satisfiability Testing

SMT

satisfiabiliy modulo theory

STP

simple temporal problem

TAL

temporal action logic

TCSP

temporal constraint satisfaction problem

TL

temporal logic

TPP

tangential proper part

VI

value iteration

W3C

WWW consortium

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Michael Beetz
    • 1
  • Raja Chatila
    • 2
  • Joachim Hertzberg
    • 3
  • Federico Pecora
    • 4
  1. 1.Institute for Artificial IntelligenceUniversity BremenBremenGermany
  2. 2.Institute of Intelligent Systems and RoboticsUniversity Pierre et Marie CurieParisFrance
  3. 3.Institute for Computer ScienceOsnabrück UniversityOsnabrückGermany
  4. 4.School of Science and TechnologyUniversity of ÖrebroÖrebroSweden

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