Wei Luo

Target Trajectory Prediction-based Object Handover in a 3D Heterogeneous Robot System


Front	Back

ISBN:

978-3-8440-9025-3

Series:

Schriften aus dem Institut für Technische und Numerische Mechanik der Universität Stuttgart
Herausgeber: Prof. Dr.-Ing. Peter Eberhard
Stuttgart

Volume:

2023,76

Keywords:

robotics; heterogeneous robot system; target trajectory prediction; discrete mechanics; model predictive control

Type of publication:

Thesis

Language:

English

Pages:

182 pages

Figures:

106 figures

Weight:

240 g

Format:

21 x 14,8 cm

Bindung:

Paperback

Price:

48,80 € / 61,10 SFr

Published:

April 2023

Buy:

DOI:

10.2370/9783844090253 (Online document)

Download:

Available PDF-Files for this title:

You need the Adobe Reader, to open the files. Here you get help and information, for the download.

These files are not printable.


	Document		Document
	Type		PDF
	Costs		36,60 EUR
	Action		Purchase in obligation and display of file - 6,6 MB (6890462 Byte)
	Action		Purchase in obligation and download of file - 6,6 MB (6890462 Byte)


	Document		Table of contents
	Type		PDF
	Costs		free
	Action		Display of file - 142 kB (144947 Byte)
	Action		Download of file - 142 kB (144947 Byte)

User settings for registered users

You can change your address here or download your paid documents again.

User:	Not logged in.
Actions:	Login / Register Forgotten your password?

Recommendation:

You want to recommend this title?

Review copy:

Here you can order a review copy.

Link:

You want to link this page? Click here.

Export citations:

Text
BibTex
RIS

Abstract:

This work is devoted to contributing multiple key-functionalities for cooperation within a heterogeneous robot group. Specifically, a hypothetical scenario is investigated, where an aerial manipulator should hand over an object from a moving mobile robot on the ground. In this cooperation, both robots are not centrally controlled. In contrast, the mobile robot is controlled separately, and the aerial manipulator can only observe the mobile robot's previous movements, and it must collaborate with the mobile robot in a more energy-efficient manner.

The first contribution of this thesis is to provide solutions for predicting the future trajectory of the observed mobile robot based on its previous movements. Once the likely future trajectory of the mobile robot is acquired, the next challenge is to plan a trajectory of the aerial manipulator to approach and implement the desired handover cooperation in a time-optimal manner without validating the aerial manipulator's dynamics. In the proposed DMCC framework, the system dynamics is constrained with the discrete variational Lagrangian mechanics, which yields reliable estimation results. Moreover, the handover opportunities are determined and arranged automatically based on the desired complementarity constraints. The last contribution of this thesis is dedicated to controlling the aerial manipulator based on nonlinear model predictive control combined with an augmented dynamic model employing Gaussian processes as a nonparametric regression model, which allows the proposed NMPC control framework to determine the optimal control inputs for the aerial manipulator and achieve a stable flight performance.