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Inverse kinematics for serial kinematic chains via sum of squares optimization

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arXiv 2019年

作者： Marić, Filip Giamou, Matthew Khoubyarian, Soroush Petrović, Ivan Kelly, Jonathan University of Toronto Institute for Aerospace Studies Space and Terrestrial Autonomous Robotic Systems Laboratory Canada University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia Vector Institute Postgraduate Affiliate and RBC Fellow

Inverse kinematics is a fundamental problem for articulated robots: fast and accurate algorithms are needed for translating task-related workspace constraints and goals into feasible joint configurations. In general, inverse kinematics for serial kinematic chains is a difficult nonlinear problem, for which closed form solutions cannot be easily obtained. Therefore, computationally efficient numerical methods that can be adapted to a general class of manipulators are of great importance. In this paper, we use convex optimization techniques to solve the inverse kinematics problem with joint limit constraints for highly redundant serial kinematic chains with spherical joints in two and three dimensions. This is accomplished through a novel formulation of inverse kinematics as a nearest point problem, and with a fast sum of squares solver that exploits the sparsity of kinematic constraints for serial manipulators. Our method has the advantages of post-hoc certification of global optimality and a runtime that scales polynomially with the number of degrees of freedom. Additionally, we prove that our convex relaxation leads to a globally optimal solution when certain conditions are met, and demonstrate empirically that these conditions are common and represent many practical instances. Finally, we provide an open source implementation of our algorithm. Copyright © 2019, The Authors. All rights reserved.

关键词： Inverse problems

Natural Criteria for Comparison of Pedestrian Flow Forecasting Models

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Natural Criteria for Comparison of Pedestrian Flow Forecasti...

2020 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Tomáš Vintr Zhi Yan Kerem Eyisoy Filip Kubiš Jan Blaha Jiří Ulrich Chittaranjan S. Swaminathan Sergi Molina Tomasz P. Kucner Martin Magnusson Gregorz Cielniak Jan Faigl Tom Duckett Achim J. Lilienthal Tomáš Krajník Artificial Intelligence Center Czech Technical University Distributed Artificial Intelligence and Knowledge Laboratory (CIAD) University of Technology of Belfort-Montbeliard (UTBM) France Faculty of Engineering Marmara University Turkey AASS Mobile Robotics and Olfaction Lab Orebro University Sweden Lincoln Centre for Autonomous Systems (L-CAS) University of Lincoln UK

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

Models of human behaviour, such as pedestrian flows, are beneficial for safe and efficient operation of mobile robots. We present a new methodology for benchmarking of pedestrian flow models based on the afforded safety of robot navigation in human-populated environments. While previous evaluations of pedestrian flow models focused on their predictive capabilities, we assess their ability to support safe path planning and scheduling. Using real-world datasets gathered continuously over several weeks, we benchmark state-of-the-art pedestrian flow models, including both time-averaged and time-sensitive models. In the evaluation, we use the learned models to plan robot trajectories and then observe the number of times when the robot gets too close to humans, using a predefined social distance threshold. The experiments show that while traditional evaluation criteria based on model fidelity differ only marginally, the introduced criteria vary significantly depending on the model used, providing a natural interpretation of the expected safety of the system. For the time-averaged flow models, the number of encounters increases linearly with the percentage operating time of the robot, as might be reasonably expected. By contrast, for the time-sensitive models, the number of encounters grows sublinearly with the percentage operating time, by planning to avoid congested areas and times.

关键词： Navigation Predictive models Benchmark testing Trajectory Planning Safety Robots

Robust Self-Scheduled Fault-Tolerant Control of a Quadrotor UAV

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IFAC-PapersOnLine 2017年第1期50卷 5761-5767页

作者： Nguyen D.-T. Saussié D. Saydy L. Mobile Robotics and Autonomous Systems Laboratory Polytechnique Montreal Canada

This paper deals with active fault-tolerant control (FTC) of a quadrotor in the presence of actuator faults. In previous studies, authors generally assume that the fault has been detected, isolated or identified and then proceed with a reconfigurable controller. This paper presents a complete active fault-tolerant control system with both fault detection and diagnosis (FDD) and FTC. The proposed FTC design is based on gain-scheduling control in the framework of structured H∞ synthesis. The scheduled gains are parameterized as polynomial functions of the loss of control effectiveness of the quadrotor's actuators, estimated by a two-stage Kalman filter. Then, the MATLAB-based function systune tune the polynomial coefficients to meet the robustness and performance requirement. In comparison with other FTC systems which use switching mechanisms, this smooth self-scheduled controller allows one to avoid undesirable transient phenomenons during the controller reconfiguration process. Numerical simulations based on an underactuated 6DoF quadrotor nonlinear model show the good effectiveness of the proposed FTC in accommodating different levels of actuator faults. © 2017

关键词： Actuator faults Fault Detection Fault-Tolerant Control Gain scheduling Quadrotor Structured H-Infinity Control Two-Stage Kalman filter

Multi-agent gaussian process motion planning via probabilistic inference ?

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arXiv 2018年

作者： Petrovic, Luka Markovic, Ivan Seder, Marija University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia

This paper deals with motion planning for multiple agents by representing the problem as a simultaneous optimization of every agent's trajectory. Each trajectory is considered as a sample from a one-dimensional continuous-time Gaussian process (GP) generated by a linear time-varying stochastic differential equation driven by white noise. By formulating the planning problem as probabilistic inference on a factor graph, the structure of the pertaining GP can be exploited to find the solution efficiently using numerical optimization. In contrast to planning each agent's trajectory individually, where only the current poses of other agents are taken into account, we propose simultaneous planning of multiple trajectories that works in a predictive manner. It takes into account the information about each agent's whereabouts at every future time instant, since full trajectories of each agent are found jointly during a single optimization procedure. We compare the proposed method to an individual trajectory planning approach, demonstrating significant improvement in both success rate and computational efficiency. Copyright © 2018, The Authors. All rights reserved.

关键词： Motion planning

autonomous Landing of a Multirotor Micro Air Vehicle on a High Velocity Ground Vehicle

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IFAC-PapersOnLine 2017年第1期50卷 10488-10494页

作者： Borowczyk A. Nguyen D.-T. Phu-Van Nguyen A. Nguyen D.Q. Saussié D. Ny J.L. Mobile Robotics and Autonomous Systems Laboratory Polytechnique Montreal and GERAD Montreal Canada

While autonomous multirotor micro aerial vehicles (MAVs) are uniquely well suited for certain types of missions benefiting from stationary flight capabilities, their more widespread usage still faces many hurdles, due in particular to their limited range and the difficulty of fully automating the deployment and retrieval. In this paper we address these issues by solving the problem of the automated landing of a quadcopter on a ground vehicle moving at relatively high speed. We present our system architecture, including the structure of our Kalman filter for the estimation of the relative position and velocity between the quadcopter and the landing pad, as well as our controller design for the full rendezvous and landing maneuvers. The system is experimentally validated by successfully landing in multiple trials a commercial quadcopter on the roof of a car moving at speeds of up to 50 km/h. © 2017

关键词： Aerospace control autonomous vehicles Computer vision Guidance systems Kalman filters mobile robots

Computationally efficient dense moving object detection based on reduced space disparity estimation

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arXiv 2018年

Computationally efficient moving object detection and depth estimation from a stereo camera is an extremely useful tool for many computer vision applications, including robotics and autonomous driving. In this paper we show how moving objects can be densely detected by estimating disparity using an algorithm that improves complexity and accuracy of stereo matching by relying on information from previous frames. The main idea behind this approach is that by using the ego-motion estimation and the disparity map of the previous frame, we can set a prior base that enables us to reduce the complexity of the current frame disparity estimation, subsequently also detecting moving objects in the scene. For each pixel we run a Kalman filter that recursively fuses the disparity prediction and reduced space semiglobal matching (SGM) measurements. The proposed algorithm has been implemented and optimized using streaming single instruction multiple data instruction set and multi-threading. Furthermore, in order to estimate the process and measurement noise as reliably as possible, we conduct extensive experiments on the KITTI suite using the ground truth obtained by the 3D laser range sensor. Concerning disparity estimation, compared to the OpenCV SGM implementation, the proposed method yields improvement on the KITTI dataset sequences in terms of both speed and accuracy. Copyright © 2018, The Authors. All rights reserved.

关键词： Computational efficiency

Manipulability maximization using continuous-time gaussian processes

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arXiv 2018年

作者： Marić, Filip Limoyo, Oliver Petrović, Luka Petrović, Ivan Kelly, Jonathan University of Toronto Institute for Aerospace Studies Space and Terrestrial Autonomous Robotic Systems laboratory Canada University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Croatia

A significant challenge in motion planning is to avoid being in or near singular configurations (singularities), that is, joint configurations that result in the loss of the ability to move in certain directions in task space. A robotic system’s capacity for motion is reduced even in regions that are in close proximity to (i.e., neighbouring) a singularity. In this work we examine singularity avoidance in a motion planning context, finding trajectories which minimize proximity to singular regions, subject to constraints. We define a manipulability-based likelihood associated with singularity avoidance over a continuous trajectory representation, which we then maximize using a maximum a posteriori (MAP) estimator. Viewing the MAP problem as inference on a factor graph, we use gradient information from interpolated states to maximize the trajectory’s overall manipulability. Both qualitative and quantitative analyses of experimental data show increases in manipulability that result in smooth trajectories with visibly more dexterous arm configurations. Copyright © 2018, The Authors. All rights reserved.

关键词： Trajectories

Motion Planning In High-Dimensional Spaces

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arXiv 2018年

作者： Petrović, Luka University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems Mobile Robotics

—Motion planning is a key tool that allows robots to navigate through an environment without collisions. The problem of robot motion planning has been studied in great detail over the last several decades, with researchers initially focusing on systems such as planar mobile robots and low degree-of-freedom (DOF) robotic arms. The increased use of high DOF robots that must perform tasks in real time in complex dynamic environments spurs the need for fast motion planning algorithms. In this overview, we discuss several types of strategies for motion planning in high dimensional spaces and dissect some of them, namely grid search based, sampling based and trajectory optimization based approaches. We compare them and outline their advantages and disadvantages, and finally, provide an insight into future research opportunities. Copyright © 2018, The Authors. All rights reserved.

关键词： Motion planning

Calibration of Heterogeneous Sensor systems

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arXiv 2018年

作者： Peršić, Juraj University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems Mobile Robotics LAMOR

Environment perception is a key component of any autonomous system and is often based on a heterogeneous set of sensors and fusion thereof for which sensor sensor calibration plays fundamental role. It can be divided to intrinsic and extrinsic sensor calibration. Former seeks for internal parameters of each individual sensor, while latter provides coordinate frame transformation between sensors. Calibration techniques require correspondence registration in the measurements which is one of the main challenges in the extrinsic calibration of heterogeneous sensors, since generally, each sensor can operate on a different physical principle. Measurement correspondences can originate from a designated calibration target or from features in the environment. Additionally, environment features can be used to estimate motion of individual sensors and the calibration is found by aligning these estimates. Motion-based calibration is the most common approach in the online calibration since it is more practical than the target-based methods, although it can lack in accuracy. Furthermore, online calibration is beneficial for system robustness as it can detect and adjust recalibration of the system in runtime, which can be seen as a prerequisite for long-term autonomy. Copyright © 2018, The Authors. All rights reserved.

关键词： Calibration