7^th ICAPS Workshop on Planning and Robotics (PlanRob)

1. Topics and Objectives

AI Planning & Scheduling (P&S) methods are crucial to enable intelligent robots to perform autonomous, flexible, and interactive behaviors, but a deep integration into robotic architectures is needed for their effective deployment. This requires a close collaboration between researchers from both the AI and the Robotics communities. In this direction, this workshop aims at constituting a stable, long-term forum where researchers from both the P&S and the Robotics communities can openly discuss about relevant issues, research and development progress, future directions and open challenges related to P&S when applied to Robotics. The PlanRob workshop is proposed in synergy with the ICAPS Robotic track. We are in contact with the Robotics Track organizers trying to explore different ways to synchronize with them. The PlanRob WS aims to maintain a more informal forum where also more preliminary/visionary works can be discussed stimulating direct and open interactions. Topics of interest include but not limited to the following:

• planning domain representations for robotics applications;
• mission, path, and motion planning for robots;
• integrated planning and execution in robotic architectures;
• planning and coordination methods for multi-robot teams;
• mixed-initiative planning and sliding autonomy for robotic systems;
• human-aware planning and execution in human-robot interaction;
• adversarial action planning in competitive robotic domains;
• formal methods for robot planning and control;
• P&S methods for optimization and adaptation in robotics;
• benchmark planning domains for robots;
• optimizing behavior in large scale automated or semi-automated systems;
• real-world planning applications for autonomous and intelligent robots.

1. Submissions

There are two types of submissions: short position statements and regular papers. Position papers are a maximum of 4 (four) pages. Regular papers are a maximum of 10 (ten) pages. All papers should be typeset in the AAAI style, described at: http://www.aaai.org/Publications/Author/author.php removing AAAI copyright. Accepted papers will be published on the workshop website and printed as a hard-copy.

The papers must be submitted in a PDF format via EasyChair system (https://easychair.org/conferences/?conf=planrob2019).

Notice that papers under review (e.g., submitted to IJCAI-2019) are also welcome, however, in order to avoid potential conflicts these manuscripts should be prepared as anonymous submissions for a double blind reviewing process. The organizers will investigate 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.

1. Important Dates

• Paper submission: March 15, 2019 (Extended: April 2, 2019)
• Notification of acceptance: April, 2019
• Camera-ready version due: June, 2019
• Workshop Date: July 11, 2019

1. Invited Speaker

Subbarao Kambhampati, Arizona State University.

Explainable Planning for Human-Robot Collaboration
As robots enter our homes and work places, there is a greater need for them work synergistically with humans. This requires the robots to exhibit behavior that is explainable to humans. Synthesizing such behavior requires the robots to reason not only with their own models of the task at hand, but also about the mental models of the human collaborators. Using several case-studies from our ongoing research, I will discuss how such multi-model planning forms the basis for explainable behavior for human-robot collaboration and teaming.

1. Schedule

• Regular papers (18 minutes slots): 15 minutes for oral presentation + 3 minutes for questions and discussions.
• Short papers (12 minutes slots): 10 minutes for oral presentation + 2 minutes for questions and discussions.

8:50 -- 9:00	Introduction
09:00 -- 10:12	Task and Motion Planning
	Minimum Time Validation for Hybrid Task Planning Ayal Taitler, Ilya Ioslovich, Erez Karpas and Per-Olof Gutman.
	Planning in Stochastic Environments with Goal Uncertainty Sandhya Saisubramanian, Kyle Wray, Luis Pineda and Shlomo Zilberstein.
	Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots Yuqian Jiang, Fangkai Yang, Shiqi Zhang and Peter Stone.
	Anytime Integrated Task and Motion Policies for Stochastic Environments Naman Shah and Siddharth Srivastava.
10:12 -- 10:30	Probabilistic Planning and Learning
	Learning Critical Regions for Robot Planning Using Convolutional Neural Networks Daniel Molina, Kislay Kumar and Siddharth Srivastava.
10:30 -- 11:00	BREAK
11:00 -- 12:00	Probabilistic Planning and Learning (continued)
	Planning Robot Motion using Deep Visual Prediction Meenakshi Sarkar, Prabhu Pradhan and Debasish Ghose.
	Towards Learning Efficient Maneuver Sets for Kinodynamic Motion Planning (short paper) Aravind Sivaramakrishnan, Zakary Littlefield and Kostas E. Bekris.
	Goal Recognition over Nominal Models Ramon Fraga Pereira, Mor Vered, Felipe Meneguzzi and Miquel Ramírez.
	Adaptive Human-Aware Task Planning (short paper) Matteo Leonetti, Luca Iocchi, Anthony G. Cohn and Daniele Nardi.
12:00 -- 12:30	Robotics Applications
	Desiderata for Planning Systems in General Purpose Service Robots (short paper) Nick Walker, Yuqian Jiang, Maya Cakmak and Peter Stone.
	Multi-Vehicle Temporal Planning for Underwater Applications Yaniel Carreno, Ronald P. A. Petrick and Yvan Petillot.
12:30 -- 14:00	LUNCH
14:00 -- 15:12	Invited Talk + Q&A
15:12 -- 15:30	Robotics Applications (continued)
	Autonomous Robotics Manipulation for In-space Intra-Vehicle Activity Shaun Azimi, Emma Zemler and Robert Morris.
15:30 -- 16:00	BREAK
16:00 -- 17:12	Robotics Applications (continued)
	Energy-Aware Data Routing for Disruption Tolerant Networks in Planetary Cave Exploration Tiago Stegun Vaquero, Martina Troesch, Marc Sanchez-Net, Jay Gao and Steve Chien.
	Scheduling with Complex Consumptive Resources for a Planetary Rover Wayne Chi, Steve Chien and Jagriti Agrawal.
	Enabling Limited Resource-Bounded Disjunction in Scheduling Jagriti Agrawal, Wayne Chi, Steve Chien, Gregg Rabideau, Stephen Kuhn and Daniel Gaines.
	Pathogen: Using Campaign Intent to Guide Onboard Planning for a Self-Reliant Rover Joseph Russino, Daniel Gaines, Steve Schaffer and Vincent Wong.
17:12 -- 18:12	Discussion and Concluding Remarks

1. Accepted Papers

• Minimum Time Validation for Hybrid Task Planning
  Ayal Taitler, Ilya Ioslovich, Erez Karpas and Per-Olof Gutman.
• Planning in Stochastic Environments with Goal Uncertainty
  Sandhya Saisubramanian, Kyle Wray, Luis Pineda and Shlomo Zilberstein.
• Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots
  Yuqian Jiang, Fangkai Yang, Shiqi Zhang and Peter Stone.
• Anytime Integrated Task and Motion Policies for Stochastic Environments
  Naman Shah and Siddharth Srivastava.
• Learning Critical Regions for Robot Planning Using Convolutional Neural Networks
  Daniel Molina, Kislay Kumar and Siddharth Srivastava.
• Planning Robot Motion using Deep Visual Prediction
  Meenakshi Sarkar, Prabhu Pradhan and Debasish Ghose.
• Towards Learning Efficient Maneuver Sets for Kinodynamic Motion Planning
  Aravind Sivaramakrishnan, Zakary Littlefield and Kostas E. Bekris.
• Goal Recognition over Nominal Models
  Ramon Fraga Pereira, Mor Vered, Felipe Meneguzzi and Miquel Ramírez.
• Adaptive Human-Aware Task Planning
  Matteo Leonetti, Luca Iocchi, Anthony G. Cohn and Daniele Nardi.
• Desiderata for Planning Systems in General Purpose Service Robots
  Nick Walker, Yuqian Jiang, Maya Cakmak and Peter Stone.
• Multi-Vehicle Temporal Planning for Underwater Applications
  Yaniel Carreno, Ronald P. A. Petrick and Yvan Petillot.
• Autonomous Robotics Manipulation for In-space Intra-Vehicle Activity
  Shaun Azimi, Emma Zemler and Robert Morris.
• Energy-Aware Data Routing for Disruption Tolerant Networks in Planetary Cave Exploration
  Tiago Stegun Vaquero, Martina Troesch, Marc Sanchez-Net, Jay Gao and Steve Chien.
• Scheduling with Complex Consumptive Resources for a Planetary Rover
  Wayne Chi, Steve Chien and Jagriti Agrawal.
• Enabling Limited Resource-Bounded Disjunction in Scheduling
  Jagriti Agrawal, Wayne Chi, Steve Chien, Gregg Rabideau, Stephen Kuhn and Daniel Gaines.
• Pathogen: Using Campaign Intent to Guide Onboard Planning for a Self-Reliant Rover
  Joseph Russino, Daniel Gaines, Steve Schaffer and Vincent Wong.

1. Organizers

• Michael Cashmore, King’s College London, U.K. (Contact: michael.cashmore@kcl.ac.uk)
• Alberto Finzi, Università di Napoli "Federico II", Italy (Contact: alberto.finzi@unina.it)
• AndreA Orlandini, National Research Council of Italy (ISTC-CNR), Italy (Contact: andrea.orlandini@istc.cnr.it)