- real-world planning applications for autonomous and intelligent robots;
- optimizing behavior 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 optimization and adaptation in robotics;
- mission, path, and motion planning for robots;
- 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;
- challenges and solutions in using P&S technology in robotics;
- open problems for P&S in robotics,
- benchmark planning domains for robots.
- Iman Awaad, Hochschule Bonn-Rhein-Sieg University of Applied Sciences, iman.awaad at h-brs.de
- Alberto Finzi, Università di Napoli "Federico II", alberto.finzi at unina.it
- AndreA Orlandini, Institute of Cognitive Sciences and Technologies (ISTC-CNR), andrea.orlandini at istc.cnr.it
Topics and Objectives
AI Planning & Scheduling (P&S) methods are key to enabling intelligent robots to perform autonomous, flexible, and interactive behaviors. 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 include (but are not limited to) the following:
Paper submission: March 7, 2021
Notification of acceptance: April 1, 2021
Camera-ready version due: May 1, 2021
Workshop Date: June 7-8, 2021
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.
There are two types of submissions: short position papers and regular papers. Position papers are a maximum of four pages long while regular papers may be up to ten pages long. 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 2021 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=planrob2021).
Please note that papers under review (e.g. which have been submitted to IJCAI-2021) 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 organizers 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.
The ICAPS PlanRob Workshop is partially supported by TAILOR "Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization", a project funded by the European Commissione (EU H2020 ICT-48 G.A. 952215).