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Software variability in service robotics.

Sergio García1, Daniel Strüber2, Davide Brugali3

  • 1University of Gothenburg | Chalmers, Gothenburg, Sweden.

Empirical Software Engineering
|January 2, 2023
PubMed
Summary
This summary is machine-generated.

Managing software variability is key for adaptable service robots. Raising abstraction levels and standardizing interfaces will improve robot software reuse, maintenance, and evolution in dynamic environments.

Keywords:
Autonomous and (self-)adaptive systemsRobotics software engineeringService robotsVariability

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Area of Science:

  • Robotics engineering
  • Software engineering
  • Artificial intelligence

Background:

  • Robotics software development is complex due to interdisciplinary needs, diverse hardware, and unpredictable environments.
  • Software variability is essential for customizing robots but introduces complexity, hindering reuse and maintenance.
  • Current ad hoc practices in robotics software variability management are insufficient.

Purpose of the Study:

  • To empirically understand variability drivers, practices, methods, and challenges in service robotics software development.
  • To analyze the state-of-the-practice and state-of-the-art in robotics software variability.
  • To provide actionable recommendations for improving robotics software engineering.

Main Methods:

  • A multiple-case study involving an experience report and eleven interviews with two industrial service robotics companies.
  • A systematic literature review to analyze the state-of-the-art in robotics software variability.
  • Triangulation of data from industry practice and literature.

Main Results:

  • The need for higher abstraction levels in robotics software to simplify variability management and integration.
  • The importance of robust abstractions and planned variability for reliable operation in dynamic, uncertain environments.
  • Current practices often rely on formalisms like finite-state machines and behavior trees for specifying robotic behavior.

Conclusions:

  • Raising abstraction levels and implementing robust abstractions are crucial for effective variability management in service robotics.
  • Standardized, hardware-decoupled software components with harmonized interfaces are vital for fostering software reuse.
  • An ecosystem for shared software components can significantly benefit the service robotics domain.