Michael Cashmore

Contact

  • Email: michael.cashmore -- at -- kcl.ac.uk
  • Skype: m312zfts

Department of Informatics,
King's College London,
Strand Building, London, UK,
WC2R 2LS

About

Michael Cashmore is a Research Associate in the Department of Informatics at King's College London. There he is a member of the Planning Group.

Research

ROSPlan

The ROSPlan framework provides a generic method for task planning in a ROS system. ROSPlan encapsulates both planning and dispatch. ROSPlan has a modular design, intended to be modified. It serves as a framework to test new modules with minimal effort. Alternate approaches to state estimation, plan representation, dispatch and execution can be tested without having to write an entire framework.

You can find more details about this on the ROSPlan website:
kcl-planning.github.io/ROSPlan/

Hybrid Planning with SMTPlan

SMTPlan+ is a planner for hybrid systems. It supports all the features of PDDL+, including exogenous events and continuous processes, providing an SMT encoding of the PDDL+ models. SMTPlan+ can handle linear domains as well as domains with nonlinear polynomial change.

PDDL+ is the extension of PDDL that allows modelling of mixed discrete-continuous domains, and it follows the Hybrid Automata semantics. Dealing with hybrid systems is becoming more and more an important challenge, as many real-world scenarios feature a mixture of discrete and continuous behaviours.

You can find more details about SMTPlan+ and source code on the project website:
http://kcl-planning.github.io/SMTPlan/

Autonomous Robots

This project is funded by the EU FP7 Project SQUIRREL.

SQUIRREL addresses clutter in an open world by actively controlling the environment, and incrementally learning to extend the robot’s capabilities while doing so. We term this the B3 (bit by bit) approach, as the robot tackles clutter one bit at a time and continuously extends its knowledge as new bits of information become available. Squirrel is inspired by a user driven scenario, that exhibits all the rich complexity required to convincingly drive research, but allows tractable solutions with high potential for exploitation.

You can find more details about this application on the project website:
http://www.squirrel-project.eu/

Underwater Robotics

This project is funded by the EU FP7 Project PANDORA.

PANDORA is a three-year project that will develop plan-based intelligent control of underwater vehicles operating for long periods without human intervention. A key goal is to significantly reduce the frequency of assistance requests. Following the Deep Water Horizon oilfield disaster in the Gulf of Mexico in 2010, contractors are developing highly actuated and hover-capable autonomous underwater vehicles (AUVs) for subsea inspection and intervention. PANDORA is focusing on automating inspection and maintenance of subsea oilfields.

You can find more details about this application in the following paper:
Planning Inspection Tasks for AUVs
M. Cashmore, M. Fox, T. Larkworthy, D. Long, D. Magazzeni.
Proceedings of OCEANS'13 MTS/IEEE.
LINK (last checked 02/04/2012)

The video below shows an early test from the first year of PANDORA. The Nessie AUV from the Ocean Systems Lab of Heriot-Watt University inspects pipes and pillars in the diver centre at Fort William, Scotland.

Publications

Cashmore, M., Coles, A. I., Cserna, B., Karpas, E., Magazzeni, D. & Ruml, W.
Situated Planning for Execution Under Temporal Constraints
Proceedings of the AAAI 2018 Spring Symposium on Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy, 2018

Cashmore, M., Coles, A. I., Cserna, B., Karpas, E., Magazzeni, D. & Ruml, W.
Temporal Planning While the Clock Ticks
Proceedings of the 28th International Conference on Automated Planning and Scheduling, 2018

Cashmore, M. Fox, M. Long, D. Magazzeni, D and Ridder, B.
Opportunistic Planning in Autonomous Underwater Missions
IEEE Transactions on Automation Science and Engineering, 2017

Cashmore, M. Fox, M. Long, D. Magazzeni, D and Ridder, B.
Short-Term Human-Robot Interaction through Conditional Planning and Execution
Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS 2017)

Cashmore, M. Fox, M. Long, D. Magazzeni, D and Ridder, B.
Strategic Planning for Autonomous Systems over Long Horizons
Proceedings of the 4th ICAPS Workshop on Planning and Robotics (PlanRob 2016)

Cashmore, M. Fox, M. Long, D. Magazzeni, D and Fox, M. Long, D. and Magazzeni, D.
Opportunistic Planning for Increased Plan Utility
Proceedings of the 4th ICAPS Workshop on Planning and Robotics (PlanRob 2016)

Cashmore, M. Fox, M. Long, D. and Magazzeni, D.
A Compilation of the Full PDDL+ Language into SMT
Proceedings of the 26th International Conference on Automated Planning and Scheduling (ICAPS 2016)

Krivic, S. Cashmore, M. Ridder, B. Magazzeni, D. Szedmak, S. Piater, J.
Initial State Prediction in Planning
Knowledge-based techniques for problem solving and reasoning (KnowProS 2017)

Krivic, S. Cashmore, M. Ridder, B. Piater, J.
Initial State Prediction in Planning
Proceedings of the 31st Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG 2016)

Cashmore, M. Fox, M. Long, D. and Magazzeni, D.
Full PDDL+ Planning through SMT
Proceedings of the AAAI Workshop on Planning for Hybrid Systems (PlanHS 2016)

N. Palomeras, A. Carrera, N. Hurts, G. C. Karras, C. P. Bechlioulis, M. Cashmore, D. Magazzeni, D. Long, M. Fox, K. J. Kyriakopoulos, P. Kormushev, J. Salvi and M. Carreras
Toward persistent autonomous intervention in a subsea panel
Autonomous Robots, 2016

Cashmore, M. Fox, M. Long, D. Magazzeni, D. Ridder, B. Maurelli, F.
Dynamically Extending Planning Models using an Ontology
Proceedings of the 2nd ICAPS Workshop on Planning and Robotics (PlanRob 2015)

Cashmore, M. Fox, M. Long, D. Magazzeni, D. Carrera, A. Palomeras, N. Hurtos, N. and Carreras, M.
ROSPlan: Planning in the Robot Operating System
Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015)

Cashmore, M. Fox, M. Long, D. Magazzeni, D. Ridder, B. Savas, E.
ROSPlan: Planning in the Robot Operating System
Proceedings of the 6th Italian Workshop on Planning and Scheduling (IPS 2015)

Cashmore, M. Fox, M. Long, D. Magazzeni, D. Ridder, B.
Articial Intelligence Planning for AUV Mission Control
Proceedings of the IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles (NGCUV 2015)

Maurelli, F. Saigol, Z. Lane, D. Cashmore, M. Ridder, B. Magazzeni, D.
On AUV actions to correctly label world information
Proceedings of the MTS/IEEE Oceans 2014 Conference, St-Johns (OCEANS 2014)

Cashmore, M. Fox, M. and Giunchiglia, E.
Encoding Reachability with Quantification
1st Workshop on Quantification (QUANTIFY 2014)
Proceedings of the Vienna Summer of Logic 2014

Cashmore, M. Fox, M. Long, D. Larkworthy, T. and Magazzeni D.
AUV Mission Control Via Temporal Planning
2014 IEEE International Conference on Robotics and Automation (ICRA 2014)

Cashmore, M. Fox, M. Long, D. and Larkworthy, T.
Planning Inspection Tasks for AUVs
Proceedings of the MTS/IEEE Oceans 2013 Conference, San Diego (OCEANS 2013)

Cashmore, M.
Planning as Quantified Boolean Formulae
PhD thesis, Department of Computer Science, University of Strathclyde, UK. (2013)

Cashmore, M. Fox, M. and Giunchiglia, E.
Partially Grounded Planning as Quantified Boolean Formula
Proceedings of the 23rd Internationsal Conference on Automated Planning and Scheduling (ICAPS 2013)

Cashmore, M. Fox, M. and Giunchiglia, E.
Planning as Quantified Boolean Formula
Proceedings of the 20th European Conference on Artificial Intelligence (ECAI 2012)

Cashmore, M. and Fox, M.
Partially Grounded Planning as Quantified Boolean Formula
Proceedings of the Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS'12)

Cashmore, M. Fox, M. and Giunchiglia, E.
Planning as Quantified Boolean Formula
Proceedings of the 29th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'11)

Cashmore, M. and Fox, M.
Planning as QBF
International Conference on Automated Planning and Scheduling Doctoral Consortium (ICAPS 2010)