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The Robot Selection Problem for Mini-Parallel Kinematic Machines: A Task-Driven Approach to the Selection Attributes

Cinzia Amici¹, Nicola Pellegrini¹, Monica Tiboni¹

¹Department of Mechanical and Industrial Engineering, University of Brescia, via Branze, 38, 25123 Brescia, Italy.

|July 26, 2020

Summary

This summary is machine-generated.

This study addresses the Robot Selection Problem (RSP) for small-scale parallel kinematic machines (PKMs). It proposes new criteria for selecting PKMs in industrial and biomedical applications, moving beyond traditional industrial robot attributes.

Keywords:

biomedical devices industrial robotics mini-manipulators parallel kinematic machines (PKM)robot kinematics and dynamics robot selection criteria task-driven design

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Area of Science:

Robotics
Decision Science
Mechanical Engineering

Background:

The Robot Selection Problem (RSP) is crucial for effectively choosing robots for specific tasks.
Existing literature primarily focuses on attributes for conventional industrial robots, neglecting specialized machines.
Identifying relevant robot attributes is key, balancing specificity with a manageable number.

Purpose of the Study:

To review and categorize existing robot attributes for the RSP.
To propose a novel set of selection criteria specifically for small-scale parallel kinematic machines (PKMs).
To evaluate these criteria for both industrial and biomedical applications.

Main Methods:

A synthetic review of current RSP literature to establish a custom taxonomy of robot attributes.
A task-driven approach comparing mini-manipulators as linear actuators.
Development and proposal of specific selection criteria for PKMs in diverse environments.

Main Results:

A custom taxonomy of robot attributes for the RSP was developed.
A set of tailored selection criteria for small-scale PKMs was proposed.
The applicability of these criteria was investigated for industrial and biomedical contexts.

Conclusions:

The proposed criteria offer a structured approach for selecting small-scale PKMs.
The task-driven methodology highlights the strengths and limitations of the attribute-based selection.
This work provides a foundation for more precise robot selection in specialized applications.