@misc{BrooksKauppMakarenko, author = {Brooks, Alex and Kaupp, Tobias and Makarenko, Alexei}, title = {Systems and methods for arranging firearms training scenarios (Patent)}, language = {en} } @misc{BrooksKauppMakarenko, author = {Brooks, Alex and Kaupp, Tobias and Makarenko, Alexei}, title = {Target device for use in a live fire training exercise and method of operating the target device (Patent)}, language = {en} } @inproceedings{KauppBrooksUpcroftetal., author = {Kaupp, Tobias and Brooks, Alex and Upcroft, Ben and Makarenko, Alexei}, title = {Building a software architecture for a human-robot team using the orca framework}, series = {Proceedings 2007 IEEE International Conference on Robotics and Automation}, booktitle = {Proceedings 2007 IEEE International Conference on Robotics and Automation}, publisher = {IEEE}, doi = {10.1109/ROBOT.2007.364051}, pages = {3736 -- 3741}, abstract = {This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a component-based software engineering approach can address these constraints. The architecture is implemented using Orca - a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the player software framework in the context of distributed systems.}, language = {en} } @misc{BrooksKauppMakarenko, author = {Brooks, Alex and Kaupp, Tobias and Makarenko, Alexei}, title = {A method of providing a live fire training environment and a moveable target for use therein (Patent)}, language = {en} } @incollection{GrocholskyMakarenkoKauppetal., author = {Grocholsky, Ben and Makarenko, Alexei and Kaupp, Tobias and Durrant-Whyte, Hugh F.}, title = {Scalable control of decentralised sensor platforms}, series = {Information Processing in Sensor Networks ; Lecture Notes in Computer Science (LNCS, Volume 2634)}, booktitle = {Information Processing in Sensor Networks ; Lecture Notes in Computer Science (LNCS, Volume 2634)}, editor = {Zhao, Feng and Guibas, Leonidas}, publisher = {Springer}, address = {Berlin, Heidelberg}, isbn = {978-3-540-02111-7}, doi = {10.1007/3-540-36978-3_7}, pages = {96 -- 112}, abstract = {This paper describes an information-theoretic approach to decentralised and coordinated control of multi-robot sensor systems. It builds on techniques long established for the related problem of Decentralised Data Fusion (DDF). The DDF architecture uses information measures to communicate state estimates in a network of sensors. For coordinated control of robot sensors, the control objective becomes maximisation of these information measures. A decentralised coordinated control architecture is presented. The approach taken seeks to achieve scalable solutions that maintain consistent probabalistic sensor fusion and payoff formulations. It inherits the many benefits of the DDF method including scalability, seamless handling of sub-system activation and deactivation, and interoperability among heterogeneous units. These features are demonstrated through application to practical multi-feature localisation problems on a team of indoor robots equipped with laser range finders.}, language = {en} } @inproceedings{BrooksKauppMakarenkoetal., author = {Brooks, Alex and Kaupp, Tobias and Makarenko, Alexei and Williams, Stefan and Oreback, Anders}, title = {Towards component-based robotics}, series = {2005 IEEE/RSJ International Conference on Intelligent Robots and Systems}, booktitle = {2005 IEEE/RSJ International Conference on Intelligent Robots and Systems}, pages = {163 -- 168}, abstract = {This paper gives an overview of component-based software engineering (CBSE), motivates its application to the field of mobile robotics, and proposes a particular component model. CBSE is an approach to system-building that aims to shift the emphasis from programming to composing systems from a mixture of off-the-shelf and custom-built software components. This paper argues that robotics is particularly well-suited for and in need of component-based ideas. Furthermore, now is the right time for their introduction. The paper introduces Orca - an open-source component-based software engineering framework proposed for mobile robotics with an associated repository of free, reusable components for building mobile robotic systems.}, language = {en} } @inproceedings{BrooksKauppMakarenko, author = {Brooks, Alex and Kaupp, Tobias and Makarenko, Alexei}, title = {Randomised MPC-based motion-planning for mobile robot obstacle avoidance}, series = {2009 IEEE International Conference on Robotics and Automation}, booktitle = {2009 IEEE International Conference on Robotics and Automation}, doi = {10.1109/ROBOT.2009.5152240}, pages = {3962 -- 3967}, abstract = {This paper presents an algorithm for real-time sensor-based motion planning under kinodynamic constraints, in unknown environments. The objective of the trajectory-generation algorithm is to optimise a cost function out to a limited time horizon. The space of control trajectories is searched by expanding a tree using randomised sampling, in a manner similar to an RRT. The algorithm is improved by seeding the tree using the best control trajectory from the previous iteration, and by pruning branches based on a bound to the cost function and the best trajectory found so far. Performance of the algorithm is analysed in simulation. In addition, the algorithm has been implemented on two kinds of vehicles: the Segway RMP and a four-wheel-drive. The algorithm has been used to drive autonomously for a combined total on the order of hundreds of hours.}, language = {en} } @inproceedings{MakarenkoBrooksKauppetal., author = {Makarenko, Alexei and Brooks, Alex and Kaupp, Tobias and Durrant-Whyte, Hugh and Dellaert, Frank}, title = {Decentralised data fusion: A graphical model approach}, series = {2009 12th International Conference on Information Fusion}, booktitle = {2009 12th International Conference on Information Fusion}, pages = {545 -- 554}, language = {en} } @inproceedings{MakarenkoBrooksKaupp, author = {Makarenko, Alexei and Brooks, Alex and Kaupp, Tobias}, title = {Orca: Components for robotics}, series = {International Conference on Intelligent Robots and Systems (IROS) - Workshop for Robotic Standardization at IROS'06}, booktitle = {International Conference on Intelligent Robots and Systems (IROS) - Workshop for Robotic Standardization at IROS'06}, pages = {163 -- 168}, abstract = {This paper describes Orca: an open-source software project which applies Component-Based Software Engineering principles to robotics. The paper focuses on the technical aspects of the framework which set it apart from other similar efforts. Among them are the adaption of a commercial middleware package, minimalist approach to framework design, and a commitment to multi-language multi-platform support. The paper explains our decision to use Ice -- a relatively recent entry in the field of general-purpose middleware packages.}, language = {en} } @article{KauppMakarenkoDurrantWhyte, author = {Kaupp, Tobias and Makarenko, Alexei and Durrant-Whyte, Hugh}, title = {Human-robot communication for collaborative decision making - A probabilistic approach}, series = {Robotics and Autonomous Systems}, volume = {5}, journal = {Robotics and Autonomous Systems}, number = {58}, doi = {10.1016/j.robot.2010.02.003}, pages = {444 -- 456}, abstract = {Humans and robots need to exchange information if the objective is to achieve a task collaboratively. Two questions are considered in this paper: what and when to communicate. To answer these questions, we developed a human-robot communication framework which makes use of common probabilistic robotics representations. The data stored in the representation determines what to communicate, and probabilistic inference mechanisms determine when to communicate. One application domain of the framework is collaborative human-robot decision making: robots use decision theory to select actions based on perceptual information gathered from their sensors and human operators. In this paper, operators are regarded as remotely located, valuable information sources which need to be managed carefully. Robots decide when to query operators using Value-Of-Information theory, i.e. humans are only queried if the expected benefit of their observation exceeds the cost of obtaining it. This can be seen as a mechanism for adjustable autonomy whereby adjustments are triggered at run-time based on the uncertainty in the robots' beliefs related to their task. This semi-autonomous system is demonstrated using a navigation task and evaluated by a user study. Participants navigated a robot in simulation using the proposed system and via classical teleoperation. Results show that our system has a number of advantages over teleoperation with respect to performance, operator workload, usability, and the users' perception of the robot. We also show that despite these advantages, teleoperation may still be a preferable driving mode depending on the mission priorities.}, language = {en} }