TY - JOUR A1 - Makarenko, Alexei A. A1 - Kaupp, Tobias A1 - Durrant-Whyte, Hugh F. T1 - Scalable human-robot interactions in active sensor networks JF - IEEE Pervasive Computing N2 - Decentralized sensor networks promise virtually unlimited scalability and can tolerate individual component failures. Interaction with human operators plays an important role in the overall system design. The authors describe an experimental active sensor network and identify modes of human-robot interaction that keep up with the network's arbitrary growth. Y1 - 2003 U6 - https://doi.org/10.1109/MPRV.2003.1251170 VL - 2 IS - 4 SP - 63 EP - 71 ER - TY - CHAP A1 - Durrant-Whyte, Hugh A1 - Sukkarieh, Salah A1 - Ramos, Fabio A1 - Bailey, Tim A1 - Kumar, Suresh A1 - Ong, Lee-Ling A1 - Ridley, Matthew A1 - Kaupp, Tobias A1 - Douillard, Bertrand A1 - Upcroft, Ben T1 - Non-gaussian state estimation in an outdoor decentralised sensor network T2 - Proceedings of the 45th IEEE Conference on Decision and Control N2 - This paper presents the development and demonstration of non-Gaussian, decentralised state estimation using an outdoor sensor network consisting of an autonomous air vehicle, a manual ground vehicle, and two human operators. The location and appearance of landmarks were estimated using bearing only observations from monocular cameras. We show that inclusion of visual and identity information aids validation gating for data association when geometric information alone cannot discriminate individual landmarks. The combination of geometric, appearance, and identity information provided a common description (or map) of natural features for each of the nodes in the network. We also show the final map from the live demonstration which includes position estimates and classification labels of the observed features. Y1 - 2006 U6 - https://doi.org/10.1109/CDC.2006.377533 SP - 366 EP - 372 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kaupp, Tobias A1 - Douillard, Bertrand A1 - Upcroft, Ben A1 - Makarenko, Alexei T1 - Hierarchical environment model for fusing information from human operators and robots T2 - 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems N2 - This paper considers the problem of building environment models by fusing information gathered by robotic platforms with human perceptual information. Rich environment models are required in real applications for both autonomous operation of robots and to support human decision making. Hierarchical models are well suited to represent complex environments because they: offer multiple abstractions of the available information to support analysis and decision-making, and permit the incorporation of higher-level human observations. The contributions of this paper are two-fold: (1) development of a probabilistic three-level environment model for distributed information gathering, and (2) experimental demonstration of fully decentralized, cooperative human-robot information gathering using an outdoor sensor network comprised of an unmanned air vehicle, a ground vehicle, and two human operators. Several information exchange patterns are presented which qualitatively demonstrate human-robot information fusion Y1 - 2006 U6 - https://doi.org/10.1109/IROS.2006.282398 SP - 5837 EP - 5842 PB - IEEE ER - TY - GEN A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Makarenko, Alexei T1 - Systems and methods for arranging firearms training scenarios (Patent) Y1 - 2014 ER - TY - CHAP A1 - Douillard, Bertrand A1 - Upcroft, Ben A1 - Kaupp, Tobias A1 - Ramos, Fabio A1 - Durrant-Whyte, Hugh T1 - Bayesian filtering over compressed appearance states T2 - Proceedings of the Australasian Conference on Robotics and Automation (ACRA) N2 - This paper presents a framework for performing real-time recursive estimation of landmarks’ visual appearance. Imaging data in its original high dimensional space is probabilistically mapped to a compressed low dimensional space through the definition of likelihood functions. The likelihoods are subsequently fused with prior information using a Bayesian update. This process produces a probabilistic estimate of the low dimensional representation of the landmark visual appearance. The overall filtering provides information complementary to the conventional position estimates which is used to enhance data association. In addition to robotics observations, the filter integrates human observations in the appearance estimates. The appearance tracks as computed by the filter allow landmark classification. The set of labels involved in the classification task is thought of as an observation space where human observations are made by selecting a label. The low dimensional appearance estimates returned by the filter allow for low cost communication in low bandwidth sensor networks. Deployment of the filter in such a network is demonstrated in an outdoor mapping application involving a human operator, a ground and an air vehicle. Y1 - 2007 UR - https://www.researchgate.net/publication/43527752_Bayesian_filtering_over_compressed_appearance_states ER - TY - GEN A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Makarenko, Alexei T1 - Target device for use in a live fire training exercise and method of operating the target device (Patent) Y1 - 2020 ER - TY - CHAP A1 - Kaupp, Tobias A1 - Brooks, Alex A1 - Upcroft, Ben A1 - Makarenko, Alexei T1 - Building a software architecture for a human-robot team using the orca framework T2 - Proceedings 2007 IEEE International Conference on Robotics and Automation N2 - 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. Y1 - 2007 U6 - https://doi.org/10.1109/ROBOT.2007.364051 SP - 3736 EP - 3741 PB - IEEE ER - TY - GEN A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Makarenko, Alexei T1 - A method of providing a live fire training environment and a moveable target for use therein (Patent) Y1 - 2018 ER - TY - CHAP A1 - Grocholsky, Ben A1 - Makarenko, Alexei A1 - Kaupp, Tobias A1 - Durrant-Whyte, Hugh F. ED - Zhao, Feng ED - Guibas, Leonidas T1 - Scalable control of decentralised sensor platforms T2 - Information Processing in Sensor Networks ; Lecture Notes in Computer Science (LNCS, Volume 2634) N2 - 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. Y1 - 2003 SN - 978-3-540-02111-7 SN - 978-3-540-36978-3 U6 - https://doi.org/10.1007/3-540-36978-3_7 SP - 96 EP - 112 PB - Springer CY - Berlin, Heidelberg ER - TY - CHAP A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Makarenko, Alexei A1 - Williams, Stefan A1 - Oreback, Anders T1 - Towards component-based robotics T2 - 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems N2 - 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. Y1 - 2005 UR - https://www.researchgate.net/publication/224623500_Towards_component-based_robotics SP - 163 EP - 168 ER - TY - CHAP A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Makarenko, Alexei T1 - Randomised MPC-based motion-planning for mobile robot obstacle avoidance T2 - 2009 IEEE International Conference on Robotics and Automation N2 - 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. Y1 - 2009 U6 - https://doi.org/10.1109/ROBOT.2009.5152240 SP - 3962 EP - 3967 ER - TY - CHAP A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Kaupp, Tobias A1 - Durrant-Whyte, Hugh A1 - Dellaert, Frank T1 - Decentralised data fusion: A graphical model approach T2 - 2009 12th International Conference on Information Fusion Y1 - 2009 SP - 545 EP - 554 ER - TY - CHAP A1 - Wang, X. Rosalind A1 - Kumar, Suresh A1 - Ramos, Fabio A1 - Kaupp, Tobias A1 - Upcroft, Ben A1 - Durrant-Whyte, Hugh T1 - Probabilistic classification of hyperspectral images by learning nonlinear dimensionality reduction mapping T2 - 2006 9th International Conference on Information Fusion Y1 - 2006 SP - 1 EP - 8 ER - TY - CHAP A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Kaupp, Tobias T1 - Orca: Components for robotics T2 - International Conference on Intelligent Robots and Systems (IROS) - Workshop for Robotic Standardization at IROS'06 N2 - 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. Y1 - 2006 SP - 163 EP - 168 ER - TY - JOUR A1 - Kaupp, Tobias A1 - Makarenko, Alexei A1 - Durrant-Whyte, Hugh T1 - Human–robot communication for collaborative decision making - A probabilistic approach JF - Robotics and Autonomous Systems N2 - 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. Y1 - 2010 U6 - https://doi.org/10.1016/j.robot.2010.02.003 VL - 5 IS - 58 SP - 444 EP - 456 ER - TY - CHAP A1 - Upcroft, Ben A1 - Ridley, Matthew A1 - Ong, Lee Ling A1 - Douillard, Bertrand A1 - Kaupp, Tobias A1 - Kumar, Suresh A1 - Bailey, Tim A1 - Ramos, Fabio A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Sukkarieh, Salah A1 - Durrant-Whyte, Hugh F. T1 - Multilevel state estimation in an outdoor decentralised sensor network T2 - 10th International Symposium on Experimental Robotics 2006 (ISER'06), Rio de Janeiro, Brazil Y1 - 2006 ER - TY - CHAP A1 - Wang, X. Rosalind A1 - Kumar, Suresh A1 - Ramos, Fabio A1 - Kaupp, Tobias A1 - Upcroft, Ben A1 - Durrant-Whyte, Hugh F. T1 - Learning in hyperspectral images using a nonlinear dimensionality reduction technique T2 - 9th International Conference on Information Fusion (Fusion 2006), Florence, Italy Y1 - 2006 ER - TY - CHAP A1 - Brooks, Alex A1 - Makarenko, Alexei A1 - Kaupp, Tobias A1 - Williams, Stefan A1 - Durrant-Whyte, Hugh F. T1 - Implementation of an indoor active sensor network T2 - 9th International Symposium on Experimental Robotics 2004, Singapore Y1 - 2004 ER - TY - CHAP A1 - Reinhart, Lukas A1 - Endres, Felix A1 - Kaupp, Tobias A1 - Willert, Volker T1 - Augmented Virtuality zur Erkennung semi-künstlicher Bilddaten T2 - Poster Session des Forums Bildverarbeitung, 24. - 25. Nov. 2022, Karlsruhe Y1 - 2022 ER - TY - CHAP A1 - Kaupp, Tobias T1 - NEWHRI: Unifying characteristics of research in human-robot interaction T2 - NEWHRI workshop at ICRA'08 Y1 - 2008 UR - https://www.researchgate.net/profile/Xavier-Giralt/publication/232746634_Robot_Behaviour_Models_in_Human_Robot_Interaction/links/09e4150938e9d48d7b000000/Robot-Behaviour-Models-in-Human-Robot-Interaction.pdf ER - TY - CHAP A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Manjunath, Meenakshi A1 - Jesus Raja, Jeshwitha A1 - Rose, Chad G. A1 - Kaupp, Tobias A1 - Daun, Marian T1 - Towards a conceptual safety planning framework for human-robot collaboration Y1 - 2023 UR - https://ceur-ws.org/Vol-3618/forum_paper_2.pdf PB - CEUR Workshop Proceedings ER - TY - JOUR A1 - Kranz, Philipp A1 - Schirmer, Fabian A1 - Kaupp, Tobias A1 - Daun, Marian T1 - Generative AI Copilot to Support Safety Analyses of Human–Robot Collaborations: Hazard Operability Analysis and GPT-4 JF - IEEE Software Y1 - 2024 U6 - https://doi.org/10.1109/MS.2024.3414445 SN - 0740-7459 VL - 41 IS - 6 SP - 65 EP - 72 PB - Institute of Electrical and Electronics Engineers (IEEE) ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Batres, Rafael A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A Peak Shaving Approach in Manufacturing Combining Machine Learning and Job Shop Scheduling T2 - Lecture Notes in Mechanical Engineering N2 - Computerized Numerical Control (CNC) plays an important role in highly autonomous manufacturing systems with multiple machine tools. The necessary Numerical Control (NC) programs to manufacture the parts are mostly written in standardized G-code. An a priori evaluation of the energy demand of CNC-based machine processes opens up the possibility of scheduling multiple jobs according to balanced energy consumption over a production period. Due to this, we present a combined Machine Learning (ML) and Job-Shop-Scheduling (JSS) approach to evaluate G-code for a CNC-milling process with respect to the energy demand of each G-command. The ML model training data are derived by the Latin hypercube sampling (LHS) method facing the main G-code operations G00, G01, and G02. The resulting energy demand for each job enhances a JSS algorithm to smooth the energy demand for multiple jobs, as peak power consumption needs to be avoided due to its expense. Y1 - 2025 SN - 9783031774287 U6 - https://doi.org/10.1007/978-3-031-77429-4_59 SN - 2195-4356 SP - 535 EP - 543 PB - Springer Nature Switzerland CY - Cham ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Deep Reinforcement Learning for Adaptive Job Shop Scheduling in Robotic Cells: Handling Disruptions Effectively T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 UR - 10.1109/ICMRE64970.2025.10976238 ER -