Planning and Robotics (PlanRob 2023)

ICAPS'23 Workshop
Prague, Czech Republic
July 9-10, 2023

Aim and Scope of the Workshop

AI Planning & Scheduling (P&S) methods are key to enabling intelligent robots to perform autonomous, flexible, and interactive behaviours. Researchers in the P&S community have continued to develop approaches and produce planners, representations, as well as heuristics that robotics researchers can make use of. However, there remain numerous challenges complicating the uptake, use and successful integration of P&S technology in robotics, many of which have been addressed by robotics researchers with novel solutions. Strong collaboration and synergy between researchers in both communities is vital to the continued growth of the fields in a way that provide mutual benefits to the two communities. To foster this, the PlanRob workshop aims to provide a stable, long-term forum (having been held annually at ICAPS since 2013) where researchers from both the P&S and Robotics communities can openly discuss relevant issues, research and development progress, future directions and open challenges related to P&S when applied to Robotics. In addition to the usual paper submissions, the workshop?s format naturally lends itself to preliminary results, position papers as well as to work focused on challenges in using and integrating planners in robotics systems.

Topics of Interest

Topics of interest include (but are not limited to):

  • coordination of multi-robot teams,
  • real-world planning applications for autonomous and intelligent robots,
  • optimising behaviour in large scale automated or semi-automated systems,
  • integrated planning and execution in robotic architectures,
  • planning domain representations for robotics applications,
  • P&S methods for optimisation and adaptation in robotics,
  • mission, path, and motion planning for robots,
  • human-aware planning and execution in human-robot interaction,
  • adversarial action planning in competitive robotic domains,
  • formal methods for robot planning and control,
  • challenges and solutions in using P&S technology in robotics,
  • open problems for P&S in robotics,
  • benchmark planning domains for robots,
  • mixed-initiative planning and sliding autonomy for robotic systems.

Important Dates

  • Paper submission: March 31, 2023 (was March 24, 2023)
  • Notification of acceptance: April 28, 2023 (was April 21, 2023)
  • Camera-ready version due: June 16
  • Workshop Date: July 09-10

The reference time-zone for all deadlines is UTC-12: Your submissions will be on time so long as there is still some place in the world where the deadline has not yet passed.

Submission Details

There are two types of submissions:

  • short position papers (four pages)
  • regular papers (up to 10 pages)

Papers may have an additional page containing references. Regular papers may be scheduled with more time in the final program. A poster session may be considered to provide a further presentation opportunity.

The guidelines for formatting are the same as is used for ICAPS 2023 papers (typeset in the AAAI style as described at: http://www.aaai.org/Publications/Author/author.php), but with the AAAI copyright removed. The papers must be submitted in PDF format via the EasyChair system (https://easychair.org/conferences/?conf=planrob23).

Please note that papers under review (e.g. which have been submitted to IJCAI-2023) are also welcome, however, in order to avoid potential conflicts, these manuscripts should be prepared as anonymous submissions for a double blind reviewing process.

Accepted papers will be published on the workshop’s website.

The organisers are investigating the availability of journal editors in order to invite a selection of accepted papers from the workshop to a special issue or post-proceedings volume.

Workshop Committee

Organizing Committee

Iman Awaad,
Hochschule Bonn-Rhein-Sieg University of Applied Sciences, Germany
iman.awaad@h-brs.de

Alberto Finzi,
Università di Napoli “Federico II”, Italy
alberto.finzi@unina.it

AndreA Orlandini,
Institute of Cognitive Sciences and Technologies (ISTC-CNR), Italy
andrea.orlandini@istc.cnr.it

Program Committee

Zlatan Ajanovic TU Delft, Netherlands
Roman Barták Charles University, Czech Republic
Riccardo Caccavale Università degli studi di Napoli Federico II, Italy
Gerard Canal King’s College London, UK
Nick Hawes University of Oxford, UK
Felix Ingrand LAAS/CNRS, France
Erez Karpas Technion, Israel
Oscar Lima German Research Center for Artificial Intelligence - DFKI, Germany
Tim Niemueller Intrinsic Innovation GmbH, Germany
Ron Petrick Heriot-Watt University, UK
Tom Silver Massachusetts Institute of Technology, USA
Mohan Sridharan University of Birmingham, UK
Charlie Street University of Birmingham, UK
Alessandro Umbrico National Research Council of Italy (CNR-ISTC), Italy

List of Accepted Papers

Ido Glanz, Matan Weksler, Erez Karpas and Tzipi Horowitz-Kraus. Robofriend: An Adpative Storytelling Robotic Teddy Bear

Magí Dalmau Moreno, Néstor García Hidalgo, Vicenç Gómez and Hector Geffner. Combined Task and Motion Planning Via Sketch Decompositions

Carlo Weidemann, Hyun-Ji Choi, Ritesh Yadav, Stefan-Octavian Bezrucav and Burkhard Corves. Capability-Aware Task Assignment for Human-Robot Teams for Empowering People with Disabilities

Elias Goldsztejn, Ronen Brafman and Tal Feiner. PTDRL: Parameter Tuning Using Deep Reinforcement Learning

Leonardo Lamanna, Luciano Serafini, Mohamadreza Faridghasemnia, Alessandro Saffiotti, Alessandro Saetti, Alfonso Emilio Gerevini and Paolo Traverso. Planning for Learning Object Properties

Phani-Teja Singamaneni, Alessandro Umbrico, Andrea Orlandini and Rachid Alami. Adaptive Robot Navigation through Integrated Task and Motion Planning

Sarah Carmesin, David Woller, David Parker, Miroslav Kulich and Masoumeh Mansouri. The Hamiltonian Cycle and Travelling Salesperson Problems with Traversal-Dependent Edge Deletion

Selvakumar Hastham Sathiya Satchi Sadanandam, Sebastian Stock, Alexander Sung, Felix Ingrand, Oscar Lima, Marc Vinci and Joachim Hertzberg. A Closed-Loop Framework-Independent Bridge from AIPlan4EU’s Unified Planning Platform to Embedded Systems

Oscar Lima Carrion, Martin Günther, Alexander Sung, Sebastian Stock, Marc Vinci, Amos Smith, Jan Christoph Krause and Joachim Hertzberg. A Physics-Based Simulated Robotics Testbed for Planning and Acting Research

Valentin Hartmann and Marc Toussaint. Towards computing low-makespan solutions for multi-arm multi-task planning problems

Sofia Santilli, Alessandro Trapasso, Luca Iocchi and Fabio Patrizi. A novel algorithm for parallelizing actions of a sequential plan

Nikhil Chandak, Kenny Chour, Sivakumar Rathinam and R Ravi. Informed Steiner Trees: Sampling and Pruning for Multi-Goal Path Finding in High Dimensions

Anthony Favier, Shashank Shekhar and Rachid Alami. Anticipating False Beliefs and Planning Pertinent Reactions in Human-Aware Task Planning with Models of Theory of Mind

David Zahrádka, Daniel Kubišta and Miroslav Kulich. Solving Robust Execution of Multi-Agent Pathfinding Plans as a Scheduling Problem

Workshop Schedule

PlanRob is scheduled on the 10th of July 2023.

[09:00 - 09:10] PlanRob WS Introduction

[09:10 - 10:10] Session 1: Human-Aware Robotics

  • Robofriend: An Adpative Storytelling Robotic Teddy Bear. Ido Glanz, Matan Weksler, Erez Karpas and Tzipi Horowitz-Kraus
  • Capability-Aware Task Assignment for Human-Robot Teams for Empowering People with Disabilities Carlo Weidemann, Hyun-Ji Choi, Ritesh Yadav, Stefan-Octavian Bezrucav and Burkhard Corves
  • Anticipating False Beliefs and Planning Pertinent Reactions in Human-Aware Task Planning with Models of Theory of Mind Anthony Favier, Shashank Shekhar and Rachid Alami

– [10:10 - 10:30] Session 2: Planning and Learning (part 1)

  • PTDRL: Parameter Tuning Using Deep Reinforcement Learning Elias Goldsztejn, Ronen Brafman and Tal Feiner

[10:30 - 11:00] - Coffee Break

[11:00 - 12:20] - Session 2: Planning and Learning (part 2)

  • Planning for Learning Object Properties Leonardo Lamanna, Luciano Serafini, Mohamadreza Faridghasemnia, Alessandro Saffiotti, Alessandro Saetti, Alfonso Emilio Gerevini and Paolo Traverso

[11:20 - 12:20] - Session 3: Task and Motion Planning

  • Combined Task and Motion Planning Via Sketch Decompositions Magí Dalmau Moreno, Néstor García Hidalgo, Vicenç Gómez and Hector Geffner
  • Adaptive Robot Navigation through Integrated Task and Motion Planning Phani-Teja Singamaneni, Alessandro Umbrico, Andrea Orlandini and Rachid Alami
  • Informed Steiner Trees: Sampling and Pruning for Multi-Goal Path Finding in High Dimensions Nikhil Chandak, Kenny Chour, Sivakumar Rathinam and R Ravi

[12:20 - 14:00] - Lunch break

[14:00 - 15:00] - “Plan-based control of robot agents – reasoning with one’s eyes and hands” Keynote speech by Michael Beetz (University of Bremen, Germany)

[15:10 - 15:30] - Session 4: Algorithms (part 1)

  • The Hamiltonian Cycle and Travelling Salesperson Problems with Traversal-Dependent Edge Deletion Sarah Carmesin, David Woller, David Parker, Miroslav Kulich and Masoumeh Mansouri

[15:30 - 16:00] - Coffee Break

[16:00 - 16:20] - Session 4: Algorithms (part 2)

  • A novel algorithm for parallelizing actions of a sequential plan Sofia Santilli, Alessandro Trapasso, Luca Iocchi and Fabio Patrizi

[16:20 - 17:40] - Session 5: Frameworks and Testbeds

  • Towards computing low-makespan solutions for multi-arm multi-task planning problems Valentin Hartmann and Marc Toussaint
  • Solving Robust Execution of Multi-Agent Pathfinding Plans as a Scheduling Problem David Zahrádka, Daniel Kubišta and Miroslav Kulich
  • A Physics-Based Simulated Robotics Testbed for Planning and Acting Research Oscar Lima Carrion, Martin Günther, Alexander Sung, Sebastian Stock, Marc Vinci, Amos Smith, Jan Christoph Krause and Joachim Hertzberg
  • A Closed-Loop Framework-Independent Bridge from AIPlan4EU’s Unified Planning Platform to Embedded Systems Selvakumar Hastham Sathiya Satchi Sadanandam, Sebastian Stock, Alexander Sung, Felix Ingrand, Oscar Lima, Marc Vinci and Joachim Hertzberg

[17:40 - 17:50] - Closing remarks

Keynote Talk

Michael Beetz (University of Bremen, Germany)

Title: Plan-based control of robot agents – reasoning with one’s eyes and hands

Abstract: Robotic agents that can accomplish manipulation tasks with the competence of humans have been one of the grand research challenges for AI planning and robotics research for more than 50 years. However, while the fields made huge progress over the years, this ultimate goal is still out of reach. I believe that this is the case because the knowledge representation and reasoning methods – including task and motion planning – that have been proposed in AI so far are necessary but too abstract. In this talk I propose to address this problem by endowing robots with the capability to internally emulate and simulate their perception-action loops based on realistic images and faithful physics simulations, which are made machine-understandable by casting them as virtual symbolic knowledge bases. These capabilities allow robots to generate huge collections of machine-understandable manipulation experiences, which robotic agents can generalize into commonsense and intuitive physics knowledge applicable to open varieties of manipulation tasks. The combination of learning, representation, reasoning, and planning will equip robots with an understanding of the relation between their motions and the physical effects they cause at an unprecedented level of realism, depth, and breadth, and enable them to master human-scale manipulation tasks. This breakthrough will be achievable by combining leading-edge simulation and visual rendering technologies with mechanisms to semantically interpret and introspect internal simulation data structures and processes. Robots with such planning and plan execution capabilities can help us to better deal with important societal, humanitarian, and economic challenges of our aging societies.