Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity

Riccardo Bertolucci; Alessio Capitanelli; Marco Maratea; Fulvio Mastrogiovanni; Mauro Vallati

doi:10.1007/978-3-030-35166-3_10

Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity

Riccardo Bertolucci, Alessio Capitanelli, Marco Maratea, Fulvio Mastrogiovanni, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

Abstract

The manipulation of articulated objects plays an important role in real-world robot tasks, both in home and industrial environments. A lot of attention has been devoted to the development of ad hoc approaches and algorithms for generating the sequence of movements the robot has to perform in order to manipulate the object. Such approaches can hardly generalise on different settings, and are usually focused on 2D manipulations.

In this paper we introduce a set of PDDL+ formulations for performing automated manipulation of articulated objects in a three-dimensional workspace by a dual-arm robot. Presented formulations differ in terms of how gravity is modelled, considering different trade-offs between modelling accuracy and planning performance, and between human-readability and parsability by planners. Our experimental analysis compares the formulations on a range of domain-independent planners, that aim at generating plans for allowing a dual-arm robot to manipulate articulated objects of different sizes. Validation is performed in simulation on a Baxter robot.

Original language	English
Title of host publication	AI*IA 2019 – Advances in Artificial Intelligence
Subtitle of host publication	XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings
Editors	Mario Alviano, Gianluigi Greco, Francesco Scarcello
Place of Publication	Cham
Publisher	Springer International Publishing AG
Pages	135-150
Number of pages	16
Volume	LNAI 11946
Edition	1st
ISBN (Electronic)	9783030351663
ISBN (Print)	9783030351656
DOIs	https://doi.org/10.1007/978-3-030-35166-3_10
Publication status	Published - 17 Nov 2019
Event	18th International Conference of the Italian Association for Artificial Intelligence - University of Calabria, Rende, Italy Duration: 19 Nov 2019 → 22 Nov 2019 Conference number: 18 https://aiia2019.mat.unical.it/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference of the Italian Association for Artificial Intelligence
Abbreviated title	AIIA 2019
Country/Territory	Italy
City	Rende
Period	19/11/19 → 22/11/19
Internet address	https://aiia2019.mat.unical.it/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-35166-3_10Licence: Other

AI_IA2019_PDDL_Accepted author manuscript, 395 KBLicence: Unspecified

Cite this

Bertolucci, R., Capitanelli, A., Maratea, M., Mastrogiovanni, F., & Vallati, M. (2019). Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity. In M. Alviano, G. Greco, & F. Scarcello (Eds.), AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings (1st ed., Vol. LNAI 11946, pp. 135-150). (Lecture Notes in Computer Science). Springer International Publishing AG. https://doi.org/10.1007/978-3-030-35166-3_10

Bertolucci, Riccardo ; Capitanelli, Alessio ; Maratea, Marco et al. / Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity. AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings. editor / Mario Alviano ; Gianluigi Greco ; Francesco Scarcello. Vol. LNAI 11946 1st. ed. Cham : Springer International Publishing AG, 2019. pp. 135-150 (Lecture Notes in Computer Science).

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title = "Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity",

abstract = "The manipulation of articulated objects plays an important role in real-world robot tasks, both in home and industrial environments. A lot of attention has been devoted to the development of ad hoc approaches and algorithms for generating the sequence of movements the robot has to perform in order to manipulate the object. Such approaches can hardly generalise on different settings, and are usually focused on 2D manipulations.In this paper we introduce a set of PDDL+ formulations for performing automated manipulation of articulated objects in a three-dimensional workspace by a dual-arm robot. Presented formulations differ in terms of how gravity is modelled, considering different trade-offs between modelling accuracy and planning performance, and between human-readability and parsability by planners. Our experimental analysis compares the formulations on a range of domain-independent planners, that aim at generating plans for allowing a dual-arm robot to manipulate articulated objects of different sizes. Validation is performed in simulation on a Baxter robot.",

keywords = "Mixed discrete-continuous planning, Robotics application",

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Bertolucci, R, Capitanelli, A, Maratea, M, Mastrogiovanni, F & Vallati, M 2019, Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity. in M Alviano, G Greco & F Scarcello (eds), AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings. 1st edn, vol. LNAI 11946, Lecture Notes in Computer Science, Springer International Publishing AG, Cham, pp. 135-150, 18th International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, 19/11/19. https://doi.org/10.1007/978-3-030-35166-3_10

Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity. / Bertolucci, Riccardo; Capitanelli, Alessio; Maratea, Marco et al.

AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings. ed. / Mario Alviano; Gianluigi Greco; Francesco Scarcello. Vol. LNAI 11946 1st. ed. Cham : Springer International Publishing AG, 2019. p. 135-150 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity

AU - Bertolucci, Riccardo

AU - Capitanelli, Alessio

AU - Maratea, Marco

AU - Mastrogiovanni, Fulvio

AU - Vallati, Mauro

N1 - Conference code: 18

PY - 2019/11/17

Y1 - 2019/11/17

N2 - The manipulation of articulated objects plays an important role in real-world robot tasks, both in home and industrial environments. A lot of attention has been devoted to the development of ad hoc approaches and algorithms for generating the sequence of movements the robot has to perform in order to manipulate the object. Such approaches can hardly generalise on different settings, and are usually focused on 2D manipulations.In this paper we introduce a set of PDDL+ formulations for performing automated manipulation of articulated objects in a three-dimensional workspace by a dual-arm robot. Presented formulations differ in terms of how gravity is modelled, considering different trade-offs between modelling accuracy and planning performance, and between human-readability and parsability by planners. Our experimental analysis compares the formulations on a range of domain-independent planners, that aim at generating plans for allowing a dual-arm robot to manipulate articulated objects of different sizes. Validation is performed in simulation on a Baxter robot.

AB - The manipulation of articulated objects plays an important role in real-world robot tasks, both in home and industrial environments. A lot of attention has been devoted to the development of ad hoc approaches and algorithms for generating the sequence of movements the robot has to perform in order to manipulate the object. Such approaches can hardly generalise on different settings, and are usually focused on 2D manipulations.In this paper we introduce a set of PDDL+ formulations for performing automated manipulation of articulated objects in a three-dimensional workspace by a dual-arm robot. Presented formulations differ in terms of how gravity is modelled, considering different trade-offs between modelling accuracy and planning performance, and between human-readability and parsability by planners. Our experimental analysis compares the formulations on a range of domain-independent planners, that aim at generating plans for allowing a dual-arm robot to manipulate articulated objects of different sizes. Validation is performed in simulation on a Baxter robot.

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DO - 10.1007/978-3-030-35166-3_10

M3 - Conference contribution

SN - 9783030351656

VL - LNAI 11946

T3 - Lecture Notes in Computer Science

SP - 135

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BT - AI*IA 2019 – Advances in Artificial Intelligence

A2 - Alviano, Mario

A2 - Greco, Gianluigi

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PB - Springer International Publishing AG

CY - Cham

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Y2 - 19 November 2019 through 22 November 2019

ER -

Bertolucci R, Capitanelli A, Maratea M, Mastrogiovanni F, Vallati M. Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity. In Alviano M, Greco G, Scarcello F, editors, AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings. 1st ed. Vol. LNAI 11946. Cham: Springer International Publishing AG. 2019. p. 135-150. (Lecture Notes in Computer Science). Epub 2019 Nov 12. doi: 10.1007/978-3-030-35166-3_10

Automated Planning Encodings for the Manipulation of Articulated Objects in 3D with Gravity

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