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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Robotic world models-conceptualization, review, and engineering best practices.

Ryo Sakagami¹, Florian S Lay¹, Andreas Dömel¹

¹Institute of Robotics and Mechatronics, DLR (German Aerospace Center), Wessling, Germany.

Frontiers in Robotics and AI

|November 29, 2023

Summary

This summary is machine-generated.

This review clarifies the definition of world models (WMs) in robotics, analyzing their design and literature across four decades. It proposes guidelines for future WM development and implementation.

Keywords:

autonomous robots environment modeling software architecture for robotics and automation state representation world model

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Area of Science:

Robotics
Artificial Intelligence
Software Engineering

Background:

The term "world model" (WM) is frequently used in robotics across various subfields.
A consistent and concise definition for WMs is lacking across domains and research fields.
Existing literature on WMs in robotics spans four decades.

Purpose of the Study:

To bootstrap a clear terminology for WMs.
To describe key design dimensions of robotic WMs.
To analyze the existing literature on WMs in robotics.

Main Methods:

Review and analysis of four decades of literature on WMs in robotics.
Application of software engineering principles (e.g., "Design for use," "Do not repeat yourself," "Low coupling, high cohesion") to motivate WMs.
Identification and description of important design dimensions for WMs.

Main Results:

A proposed terminology and definition for WMs.
Analysis of WMs in robotics based on identified design dimensions.
Highlighting similarities and differences in WM applications between mobile manipulation and deep reinforcement learning.

Conclusions:

WMs are crucial in robotics, but require standardized definitions and design principles.
Software engineering principles offer valuable insights for developing robust WMs.
Future research should focus on concrete design guidelines for WMs to enhance their development and implementation.