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  • 1.
    Båberg, Fredrik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Wang, Yuquan
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Caccamo, Sergio
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Adaptive object centered teleoperation control of a mobile manipulator2016In: 2016 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 455-461Conference paper (Refereed)
    Abstract [en]

    Teleoperation of a mobile robot manipulating and exploring an object shares many similarities with the manipulation of virtual objects in a 3D design software such as AutoCAD. The user interfaces are however quite different, mainly for historical reasons. In this paper we aim to change that, and draw inspiration from the 3D design community to propose a teleoperation interface control mode that is identical to the ones being used to locally navigate the virtual viewpoint of most Computer Aided Design (CAD) softwares.

    The proposed mobile manipulator control framework thus allows the user to focus on the 3D objects being manipulated, using control modes such as orbit object and pan object, supported by data from the wrist mounted RGB-D sensor. The gripper of the robot performs the desired motions relative to the object, while the manipulator arm and base moves in a way that realizes the desired gripper motions. The system redundancies are exploited in order to take additional constraints, such as obstacle avoidance, into account, using a constraint based programming framework.

  • 2.
    Ji, Wei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Yuquan
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Hongyi
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Interface architecture design for minimum programming in human-robot collaboration2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, Vol. 72, p. 129-134Conference paper (Refereed)
    Abstract [en]

    Many metal components, especially large-sized ones, need to be ground or deburred after turning or milling to improve the surface qualities, which heavily depends on human interventions. Robot arms, combining movable platforms, are applied to reduce the human work. However, robots and human should work together due to the fact that most of the large-sized parts belong to small-batch products, resulting in a large number of programming for operating a robot and movable platform. Targeting the problem, this paper proposes a new interface architecture towards minimum programming in human-robot collaboration. Within the context, a four-layer architecture is designed: user interface, function block (FB), functional modules and hardware. The user interface is associated with use cases. Then, FB, with embedded algorithms and knowledge and driven by events, is to provide a dynamic link to the relevant application interface (APIs) of the functional modules in terms of the case requirements. The functional modules are related to the hardware and software functions; and the hardware and humans are considered in terms of the conditions on shop floors. This method provides three-level applications based on the skills of users: (1) the operators on shop floors, can operate both robots and movable platforms programming-freely; (2) engineers are able to customise the functions and tasks by dragging/dropping and linking the relevant FBs with minimum programming; (3) the new functions can be added by importing the APIs through programming.

  • 3.
    Liu, Hongyi
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Sustainable production development.
    Fang, Tongtong
    KTH.
    Zhou, Tianyu
    KTH.
    Wang, Yuquan
    KTH, School of Industrial Engineering and Management (ITM), Sustainable production development.
    Wang, Lihui
    Deep Learning-based Multimodal Control Interface for Human-Robot Collaboration2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, Vol. 72, p. 3-8Conference paper (Refereed)
    Abstract [en]

    In human-robot collaborative manufacturing, industrial robot is required to dynamically change its pre-programmed tasks and collaborate with human operators at the same workstation. However, traditional industrial robot is controlled by pre-programmed control codes, which cannot support the emerging needs of human-robot collaboration. In response to the request, this research explored a deep learning-based multimodal robot control interface for human-robot collaboration. Three methods were integrated into the multimodal interface, including voice recognition, hand motion recognition, and body posture recognition. Deep learning was adopted as the algorithm for classification and recognition. Human-robot collaboration specific datasets were collected to support the deep learning algorithm. The result presented at the end of the paper shows the potential to adopt deep learning in human-robot collaboration systems.

  • 4.
    Liu, Hongyi
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Yuquan
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A Context-Aware Safety System for Human-Robot Collaboration2018In: Procedia Manufacturing, Elsevier B.V. , 2018, p. 238-245Conference paper (Refereed)
    Abstract [en]

    Recent advancements in human-robot collaboration have enabled humans and robots to work together in shared manufacturing environment. However, there still exist needs for a context-aware safety system that not only assures human safety but also provides system efficiency. In this paper, the authors present a context-aware safety system that provides safety and efficiency at the same time. The system can plan robotic paths that avoid colliding with humans while still reach target positions in time. Human poses can also be recognised by the system to further increase system efficiency. Different modules, algorithms, and interfaces are introduced in the paper to support the context-aware safety system for human-robot collaboration. A test case is demonstrated to validate the performance of the system. Finally, a summary and future research directions are given.

  • 5.
    Liu, Sichao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Yuquan
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Energy-efficient trajectory planning for an industrial robot using a multi-objective optimisation approach2018Conference paper (Refereed)
    Abstract [en]

    This paper presents an approach for energy-efficient trajectory planning of an industrial robot. A model that can be used to formulate the energy consumption of the robot with the kinematics constraints is developed. Given the trajectory in the Cartesian space, the septuple B-spline is applied in joint space trajectory planning to make the velocities, accelerations, and jerks bounded and continuous, with constraints on the initial and ending values. Then, energy-efficient optimisation problem with nonlinear constraints is discussed. Simulation results show that, the proposed approach is effective solution to trajectory planning, with ensuring a good energy improvement and fluent movement for the robot manipulators.

  • 6.
    Liu, Yongkui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Yuquan
    KTH.
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Zhang, L.
    China.
    Multi-agent-based scheduling in cloud manufacturing with dynamic task arrivals2018In: Procedia CIRP, Elsevier, 2018, p. 953-960Conference paper (Refereed)
    Abstract [en]

    Scheduling is a critical means for providing on-demand manufacturing services in cloud manufacturing. Multi-agent technologies provide an effective approach for addressing scheduling issues in cloud manufacturing, which, however, have rarely been used for solving the issue. This paper addresses scheduling issues in cloud manufacturing using multi-agent technologies. A multi-agent architecture for scheduling in cloud manufacturing is proposed firstly. Then, a corresponding multi-agent model is presented, which incorporates many-to-many negotiations based on an extended contract net protocol and takes into account dynamic task arrivals. Simulation results indicate the feasibility of the model and approach proposed.

  • 7.
    Wang, Yuquan
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Reactive control and coordination of redundant robotic systems2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Redundant robotic systems, in terms of manipulators with one or twoarms, mobile manipulators, and multi-agent systems, have received an in-creasing amount of attention in recent years. In this thesis we describe severalways to improve robotic system performance by exploiting the redundancy.

    As the robot workspace becomes increasingly dynamic, it is common towork with imperfect geometric models of the robots or its workspace. Inorder to control the robot in a robust way in the presence of geometric uncer-tainties, we propose to assess the stability of our controller with respect to acertain task by deriving bounds on the geometric uncertainties. Preliminaryexperimental results support the fact that stability is ensured if the proposedbounds on the geometric uncertainties are fulfilled.

    As a non-contact measurement, computer vision could provide rich infor-mation for robot control. We introduce a two step method that transformsthe position-based visual servoing problem into a quadratic optimization prob-lem with linear constraints. This method is optimal in terms of minimizinggeodesic distance and allows us to integrate constraints, e.g. visibility con-straints, in a natural way.

    In the case of a single robot with redundant degrees of freedom, we canspecify a family of complex robotic tasks using constraint based programming(CBP). CBP allows us to represent robotic tasks with a set of equality andinequality constraints. Using these constraints we can formulate quadraticprogramming problems that exploit the redundancy of the robot and itera-tively resolve the trade-off between the different constraints. For example, wecould improve the velocity or force transmission ratios along a task-dependent direction using the priorities between different constraints in real time.

    Using the reactiveness of CBP, we formulated and implemented a dual-armpan cleaning task. If we mount a dual-arm robot on a mobile base, we proposeto use a virtual kinematic chain to specify the coordination between the mobilebase and two arms. Using the modularity of the CBP, we can integrate themobility and dual-arm manipulation by adding coordination constraints intoan optimization problem where dual-arm manipulation constraints are alreadyspecified. We also found that the reactiveness and modularity of the CBPapproach is important in the context of teleoperation. Inspired by the 3Ddesign community, we proposed a teleoperation interface control mode thatis identical to the ones being used to locally navigate the virtual viewpoint ofmost Computer Aided Design (CAD) softwares.

    In the case of multiple robots, we combine ideas from multi-agent coopera-tive coverage control, with problem formulations from the resource allocationfield, to create a distributed convergent approach to the resource positioningproblem.

  • 8.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Kostić, Dragan
    Eindhoven University of Technology, Eindhoven.
    Jansen, Sven T.H
    TNO, Helmond.
    Nijmeijer, Henk
    Eindhoven University of Technology, Eindhoven.
    Filling the gap between low frequency measurements with their estimates2014In: Robotics and Automation (ICRA), 2014 IEEE International Conference on, IEEE conference proceedings, 2014, p. 175-180Conference paper (Refereed)
    Abstract [en]

    The use of redundant sensors brings a rich diver-sity of information, nevertheless fusing different sensors thatrun at vastly different frequencies into a proper estimate isstill a challenging sensor fusion problem. Instead of using thesize-varying measurements and thereby the size-varying filtersduring each sampling period, we propose to find a substitute ofthe unavailable low frequency measurements such that we canavoid using different sampling frequencies in one filter. In thegap between the sampling of two low frequency measurements,the use of these substitutes produces smoother estimates. In boththe proof of concept simulation and the localization experimentperformed on an indoor soccer robot, our proposed approachexhibits an improved performance compared to the size-varyingKalman filter methods.

  • 9.
    Wang, Yuquan
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Hongyi
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Realtime collaborating with an industrial manipulator using a constraint-based programming approach2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, p. 105-110Conference paper (Refereed)
    Abstract [en]

    Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different from the well-defined structured environment, safe robot control in a workspace with moving objects, e.g. a human, requires us to control the robot motion on the fly. In order to computationally efficiently achieve a feasible solution, we propose a constraint-based programming approach to guarantee the safe human-robot interaction. We use an optimization framework to integrate constraints from two-fold: the robot control constraints that are responsible for a generic robotic task and the online formulated safety constraints that are responsible for safe human-robot interaction. In this way, we preserve the task execution ability of a robot while guarantee the safe human-robot interaction. We validate the proposed approach with a Schunk industrial manipulator. The experimental results confirms the fact that the proposed approach has the potential to enable an industrial manipulator to work with a human coworker side-by-side.

  • 10.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Ogren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Smith, Christian
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Vina, Francisco
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Karayiannidis, Yiannis
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Dual Arm Manipulation using ConstraintBased Programming2014In: Proceedings of the 19th World CongressThe International Federation of Automatic Control / [ed] Boje, Edward, Xia, Xiaohua, 2014, Vol. 19, p. 311-319Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a technique for online generation of dual arm trajectories using constraint based programming based on bound margins. Using this formulation, we take both equality and inequality constraints into account, in a way that incorporates both feedback and feedforward terms, enabling e.g. tracking of timed trajectories in a new way. The technique is applied to a dual arm manipulator performing a bi-manual task. We present experimental validation of the approach, including comparisons between simulations and real experiments of a complex bimanual tracking task. We also show how to add force feedback to the framework, to account for modeling errors in the systems. We compare the results with and without feedback, and show how the resulting trajectory is modified to achieve the prescribed interaction forces.

  • 11.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Smith, Christian
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Karayiannidis, Yiannis
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Whole Body Control of a Dual-Arm Mobile Robot Using a Virtual Kinematic Chain2016In: INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, ISSN 0219-8436, Vol. 13, no 1, article id 1550047Article in journal (Refereed)
    Abstract [en]

    Dual-arm manipulators have more advanced manipulation abilities compared to single-arm manipulators and manipulators mounted on a mobile base have additional mobility and a larger workspace. Combining these advantages, mobile dual-arm robots are expected to perform a variety of tasks in the future. Kinematically, the configuration of two arms that branches from the mobile base results in a serial-to-parallel kinematic structure. In order to respond to external disturbances, this serial-to-parallel kinematic structure makes inverse kinematic computations non-trivial, as the motion of the base has to take the needs of both arms into account. Instead of using the dual-arm kinematics directly, we propose to use a virtual kinematic chain (VKC) to specify the common motion of the two arms. We formulate a constraint-based programming solution which consists of two parts. In the first part, we use an extended serial kinematic chain including the mobile base and the VKC to formulate constraints that realize the desired orientation and translation expressed in the world frame. In the second part, we use the resolved VKC motion to constrain the common motion of the two arms. In order to explore the redundancy of the two arms in an optimization framework, we also provide a VKC-oriented manipulability measure as well as its closed-form gradient. We verify the proposed approach with simulations and experiments that are performed on a PR2 robot, which has two 7 degrees of freedom (DoF) arms and a 3 DoF mobile base.

  • 12.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Smith, Christian
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Karayiannidis, Ioannis
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Cooperative control of a serial-to-parallel structure using a virtual kinematic chain in a mobile dual-arm manipulation application2015In: Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, Hamburg, Germany: IEEE Robotics and Automation Society, 2015, p. 2372-2379Conference paper (Refereed)
    Abstract [en]

    In the future mobile dual-arm robots are expected to perform many tasks. Kinematically, the configuration of two manipulators that branch from the same common mobile base results in a serial-to-parallel kinematic structure, which makes inverse kinematic computations non-trivial. The motion of the base has to be decided in a trade-off, taking the needs of both arms into account. We propose to use a Virtual Kinematic Chain (VKC) to specify the common motion of the parallel manipulators, instead of using the two manipulators kinematics directly. With this VKC, we formulate a constraint based programming solution for the robot to respond to external disturbances during task execution. The proposed approach is experimentally verified both in a noise-free illustrative simulation and a real human robot co-manipulation task.

  • 13.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Thunberg, Johan
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Hu, Xiaoming
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    A transformation of the Position Based Visual Servoing Problem into a convex optimization problem2012In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC), IEEE , 2012, p. 5673-5678Conference paper (Refereed)
    Abstract [en]

    Here we address the problem of moving a camera from an initial pose to a final pose. The trajectory between the two poses is subject to constraints on the camera motion and the visibility, where we have bounds on the allowed velocities and accelerations of the camera and require that a set of point features are visible for the camera. We assume that the pose is possible to retrieve from the observations of the point features, i.e., we have a Position Based Visual Servoing Problem with constraints. We introduce a two step method that transforms the problem into a convex optimization problem with linear constraints. In the first step the rotational motion is restricted to be of a certain type. This restriction allows us to retrieve an explicit solution of the rotational motion that is optimal in terms of minimizing geodesic distance. Furthermore, this restriction guarantees that the rotational motion satisfies the constraints. Using the explicit solution, we can formulate a convex optimization problem for the translational motion, where we include constraints on workspace and visibility.

  • 14.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Vina, Francisco
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Karayiannidis, Yiannis
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Smith, Christian
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Whole body control of a dual-arm mobile robot using a virtual kinematic chain2014Manuscript (preprint) (Other academic)
  • 15.
    Wang, Yuquan
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Applicability analysis of generalized inverse kinematics algorithms with respect to manipulator geometric uncertainties2017In: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Bicchi, A Okamura, A, IEEE , 2017, p. 2813-2820Conference paper (Refereed)
    Abstract [en]

    Accurate kinematic models and measurements are needed in many robotic applications. However uncertainties related to joint angle measurements and manipulator geometry are unavoidable, especially when grasping and using different tools or when we do not have access to an accurate robot model, e.g. when we construct a robotic system by hand. The generalized inverse kinematics methods are not applicable when a manipulator stay inside its singular region. We derive the upper bounds on the joint measurement errors and geometric uncertainties, in order to guarantee that the open-chain serial manipulators stay outside the singular region. These bounds in other words enable en effective execution of generalized inverse kinematics methods for a robotic system which is prone to geometric uncertainties. In addition to the analytic derivation, We validate the proposed bounds through a trajectory tracing task performed by a PR2 robot simulator.

  • 16.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Reactive task-oriented redundancy resolution using constraint-based programming2016In: IEEE International Conference on Intelligent Robots and Systems, IEEE, 2016, p. 5689-5694Conference paper (Refereed)
    Abstract [en]

    Constraint based programming provides a versatile framework for combining several different constraints into a single robot control scheme. We take advantage of the redundancy of a robot manipulator to improve the execution of a reactive tracking task, in terms of a task-dependent measure which is a weighted sum of velocity transmissions along the current directions of motion. With inspiration from recent work, we provide analytical gradients and computable weights of the task-dependent measure, which enable us to include it in a reactive constraint based programming framework, without relying on inexact numerical approximations and manually tuning weights. The proposed approach is illustrated in a set of simulations, comparing the performance with a standard constraint based programming method.

  • 17.
    Wang, Yuquan
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Resolve reactive robot control with perturbed constraints using a second order cone programming approach2017In: 2017 13TH IEEE CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), IEEE , 2017, p. 124-129Conference paper (Refereed)
    Abstract [en]

    As a modular and reactive control approach, constraint-based programming helps us to formulate and solve complex robotic tasks in a systematic way. In different fields ranging from industrial manipulators to humanoids, robots are supposed to work in an uncertain environment. However, how to address uncertainties is missing in the state-of-the-art of different constraint-based programming frameworks. In this paper, we introduce a Second Order Cone Programming (SOCP) approach to integrate constraints with norm bounded uncertainties. The proposed SOCP is convex and through simulations with controlled uncertainty level, we can clearly tell that the proposed approach guarantees the constraints satisfaction compared to the state-of-the-art.

  • 18.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Singularity analysis of closed-loop inverse kinematics algorithms with respect to manipulator geometric uncertainties2014Manuscript (preprint) (Other academic)
  • 19.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Ögren, Petter
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Colledanchise, Michele
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Marzinotto, Alejandro
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    A Distributed Convergent Solution to the Ambulance Positioning Problem on a Streetmap Graph2014In: / [ed] Boje, Edward, Xia, Xiaohua, IFAC Papers Online, 2014, Vol. 19, p. 9190-9196Conference paper (Refereed)
    Abstract [en]

    In this paper, we combine ideas from multi-agent cooperative coverage control, with problem formulations from the resource allocation field, to create a distributed convergent approach to the ambulance positioning problem. Inspired by coverage control we use the graph version of so-called Voronoi regions, making the solution distributed and reactive, thereby freeing computational resources. The solution is distributed in the sense that each vehicle only needs to know the positions of its neighbors, and the computations of each vehicle only depend on the size of its Voronoi region/set. This implies that considering a problem of twice the size, using twice the number of vehicles will leave the computational load per vehicle unchanged. The freed resources are used to capture the allocation problem in more detail: maximizing an estimate of the victim survival probability instead of more coarse measures of ambulance availability. Using real city street map data from OpenStreetMap (OSM), we provide simulation results illustrating the applicability of our approach. Finally, we prove that the proposed distributed algorithm is convergent in the sense that it finds a local optimum in finite time.

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