Realization of a Cooperative Human-Robot-Picking by a Learning Multi-Robot-System Using BDI-Agents

18 Pages Posted: 1 Jan 2020

See all articles by Richard Verbeet

Richard Verbeet

Technische Hochschule Ulm

Mathias Rieder

Technische Hochschule Ulm

Martin Kies

LeverageData GmbH; Ulm University

Date Written: December 12, 2019

Abstract

This article presents a process model for a picking environment which allows robots and humans to collaborate while simultaneously allowing the robots to increase their performance through directed integration of human feedback. Our approach is an adaptive multi-robot-system based on Active Component Shells to handle the automatic detection and gripping of objects. The learning and picking processes are guided by a warehouse management system and are supported by a computation cluster. The system integrates human pickers into these processes to support robotic learning and to ensure process stability as a fallback. The picking robots and the IT systems are realized by a BDI multiagent-system communicating via MQTT.

Keywords: picking system, multi-robot-system, multiagent-system, human-robot-cooperation, machine learning, object recognition

Suggested Citation

Verbeet, Richard and Rieder, Mathias and Kies, Martin, Realization of a Cooperative Human-Robot-Picking by a Learning Multi-Robot-System Using BDI-Agents (December 12, 2019). Available at SSRN: https://ssrn.com/abstract=3502934 or http://dx.doi.org/10.2139/ssrn.3502934

Richard Verbeet (Contact Author)

Technische Hochschule Ulm ( email )

Prittwitzstraße 10
Ulm, Baden-Württemberg 89075
Germany

Mathias Rieder

Technische Hochschule Ulm ( email )

Prittwitzstraße 10
Ulm, Baden-Württemberg 89075
Germany

Martin Kies

LeverageData GmbH ( email )

Wagnerstr. 18
Ulm, 89077
Germany
+4973129879770 (Phone)

Ulm University ( email )

Helmholtzstr. 18
Ulm, Baden-Württemberg 89081
Germany
7315015367 (Phone)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
41
Abstract Views
210
PlumX Metrics