Thomas Larkworthy PhD

Thomas Larkworthy


Publications:
2011
  A characterization of the reconfiguration space of self-reconfiguring robotic systems
Larkworthy, T & Ramamoorthy, S 2011, 'A characterization of the reconfiguration space of self-reconfiguring robotic systems' Robotica, vol 29, no. Special Issue 1, pp. 73-85. DOI: 10.1017/S0263574710000718
Motion planning for self-reconfiguring robots can be made efficient by exploiting potential reductions to suitably large subspaces. However, there are no general techniques for identifying suitable restrictions that have a positive effect on planning efficiency. We present two approaches to understanding the structure that is required of the subspaces, which leads to improvement in efficiency of motion planning. This work is presented in the context of a specific motion planning procedure for a hexagonal metamorphic robot. First, we use ideas from spectral graph theory -- empirically estimating the algebraic connectivity of the state space -- to show that the HMR model is better structured than many alternative motion catalogs. Secondly, using ideas from graph minor theory, we show that the infinite sequence of subspaces generated by configurations containing increasing numbers of subunits is well ordered, indicative of regularity of the space as complexity increases. We hope that these principles could inform future algorithm design for many different types of self-reconfiguring robotics problems.
General Information
Organisations: Institute of Perception, Action and Behaviour .
Authors: Larkworthy, Tom & Ramamoorthy, Subramanian.
Keywords: (Self-reconfiguring robotics, Motion planning, Graph theory, , , . )
Number of pages: 13
Pages: 73-85
Publication Date: Jan 2011
Publication Information
Category: Article
Journal: Robotica
Volume: 29
Issue number: Special Issue 1
ISSN: 0263-5747
Original Language: English
DOIs: 10.1017/S0263574710000718
2010
  Algorithms for automatic neuron tracing in noisy 3D image stacks
Knowles-Barley, S, Phillipson, G, Teriakidis, A, Sterratt, D, Larkworthy, T, O'Leary, T, Down, MP, Hennig, M, Withers, JPJ & Hull, M 2010, 'Algorithms for automatic neuron tracing in noisy 3D image stacks' Neuroscience Day 2010, Edinubrgh, United Kingdom, 29/03/10 - 29/03/10, .
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Knowles-Barley, Seymour, Phillipson, Graeme, Teriakidis, Adrianna, Sterratt, David, Larkworthy, Thomas, O'Leary, Timothy, Down, Matthew P., Hennig, Matthias, Withers, James P. J. & Hull, Michael.
Publication Date: 2010
Publication Information
Category: Poster
Original Language: English
  An efficient algorithm for self-reconfiguration planning in a modular robot
Larkworthy, T & Ramamoorthy, S 2010, An efficient algorithm for self-reconfiguration planning in a modular robot. in Robotics and Automation (ICRA), 2010 IEEE International Conference on.
An efficient planning algorithm for the hexagonal metamorphic self-reconfiguring system (SRS) is presented. Empirically, the algorithm achieves an time complexity of O(n) averaged over random problem instances. The planning algorithm is capable of solving approximately 97% of planning tasks in the general state space of configurations containing less than 20,000 units. The state space is divided into two classes according to planning efficiency. The configurations belonging to the first class permit an Euler tour to be wrapped around the robotic aggregate. The existence of the Euler tour implies units are free to move around the perimeter of the SRS. Planning between configurations in this class can be performed in O(n) using a specialized planning algorithm. The set of Euler tour configurations span a large volume of the general state space of the hexagonal SRS. A second specialized planning algorithm plans from a general configuration to a nearby Euler tour configuration. While planning in the general configuration state space is computationally harder, the distance required to plan is short. Thus, the combination of both algorithms allows us to efficiently plan for a large proportion of possible reconfiguration tasks for the hexagonal metamorphic robot.
General Information
Organisations: Institute of Perception, Action and Behaviour .
Authors: Larkworthy, Thomas & Ramamoorthy, Subramanian.
Publication Date: 2010
Publication Information
Category: Conference contribution
Original Language: English
  Graph minor analysis of reconfiguration state spaces
Larkworthy, T & Ramamoorthy, S 2010, Graph minor analysis of reconfiguration state spaces. in ICRA 2010 Workshop on Modular Robots.
Efficiently overcoming difficult motion constraints is the prime problem in development of efficient motion planning algorithms for self-reconfiguring systems (SRSs). Metamodularization, and other related techniques, deal with the problem by adding further constraints in a way that simplifies planning. If Rn denotes a raw state space for configurations containing n sub-units, and Cn a further constrained version of Rn then Rn le Cn where le denotes the graph minor relation. Often the choice of Cn is ad hoc (although made on clever intuitions). We wish to study whether there are principles that may guide this choice. We demonstrate one such principle, that is planning is tractable, e.g. in meta-modularized sub-spaces, when Cn le Cn+1, which captures a smooth increase in state-space complexity as more modules are added.
General Information
Organisations: Institute of Perception, Action and Behaviour .
Authors: Larkworthy, Thomas & Ramamoorthy, Subramanian.
Publication Date: 2010
Publication Information
Category: Conference contribution
Original Language: English
2009
  General Motion Planning Methods for Self-Reconfiguration Planning
Larkworthy, T, Hayes, G & Ramamoorthy, S 2009, General Motion Planning Methods for Self-Reconfiguration Planning. in Towards Autonomous Robotic Systems (TAROS 2009).
Self-reconfiguring robotic systems (SRSs) can alter their morphology autonomously. Determining a feasible plan of subcomponent moves that realize a desired shape, in general, is a hard problem for which there are no general solutions. We investigated the utility of some general motion planning methods, namely greedy search, RRT-Connect (RRT), probabilistic roadmaps (PRM) and simulated annealing (SA), as part of an investigation into generally applicable techniques for different SRS architectures. The performance of such methods is greatly dependent on heuristics. We present two new heuristics that improve performance, a greedy assignment heuristic which is a faster approximation to the classic optimal assignment heuristic, and the vector map heuristic, which transforms a configuration into a vector representation for fast nearest neighbor queries. Results of our experiments show greedy search is the fastest single shot planning algorithm for two variants of the hexagonal metamorphic system. Probabilistic roadmap planning is the fastest method overall, but initial roadmap construction is expensive. Also, we applied two existing post processing smoothing algorithms whose combination significantly improves plans produced by RRT, SA and PRM.
General Information
Organisations: Institute of Perception, Action and Behaviour .
Authors: Larkworthy, Thomas, Hayes, Gillian & Ramamoorthy, Subramanian.
Publication Date: 2009
Publication Information
Category: Conference contribution
Original Language: English
  Utilizing Redundancy in Modular Robots to Achieve Greater Accuracy
Larkworthy, T & Hayes, G 2009, Utilizing Redundancy in Modular Robots to Achieve Greater Accuracy. in ROBOCOMM (Second International Conference on Robot Communication and Coordination 2009).
Modular robot configurations typically feature many kinematically redundant loops. We believe that the information in these loops can be utilized in order to increase the accuracy of localization, in particular, at an end effector. We hope it will be possible to design an algorithm that can design configurations able to manipulate to a user specified level of accuracy. In order to do so, it would be necessary to predict the level of accuracy of a configuration from a priori information. In this work we provide experimental evidence that increased accuracy is easily achieved through redundancy. We then formulate a representation of accuracy as a distribution of location across space. We use Bayesian statistics to prototype three different models of the experimental system and test their ability to predict the increase in accuracy observed. We find that all three of the statistics prototyped were conservative estimators, leading us to the conclusion that our kinematic model of the system was too constrained.
General Information
Organisations: School of Informatics.
Authors: Larkworthy, Thomas & Hayes, Gillian.
Publication Date: 2009
Publication Information
Category: Conference contribution
Original Language: English

Projects:
RSE/SE Enterprise Fellowship 2010
Thomas, Larkworthy (Principal investigator)
Period: 30/04/201029/04/2011
Funding Organisation: UK-based charities

Projects:
A flexible lattice-based self-reconfigurable robot (PhD)