Library
local_library Home Repository

A Systems Engineering Analysis of Robot Motion for Team Delft’s APC Winner 2016

Book Chapter (2020)
Author(s)

Carlos Hernandez Corbato (TU Delft - Robust Robot Systems)

Mukunda Bharatheesha (Caspar AI B.V)

Research Group
Robust Robot Systems
DOI related publication
https://doi.org/10.1007/978-3-030-35679-8_7
More Info
expand_more
Publication Year
2020
Language
English
Research Group
Robust Robot Systems
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/publishing/publisher-deals Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
73-85
Publisher
Springer
ISBN (print)
978-3-030-35678-1
ISBN (electronic)
978-3-030-35679-8
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

In this chapter we take a systems engineering stand to perform a postmortem analysis of the design of the robot motion subsystem in Team Delft’s robot winner of the Amazon Picking Challenge 2016, understanding the benefits and limitations of the motion planning approach taken. We use an analysis framework based on Model-Based Systems Engineering with the ISEandPPOOA methodology, and a novel model of levels of robot automation. The functional approach of ISEandPPOOA helps us understand how the design decisions in the architecture of the solution impact the performance and quality attributes in capabilities required for the competition. The levels of robot automation help analyze the fundamental properties of the control schemas applied at different levels of the control architecture when handling uncertainty.

Files

978-3-030-35679-8_7.pdf
(pdf | 0.477 Mb)
- Embargo expired in 09-11-2020
License info not available