机器人相关学术速递[8.30]

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cs.RO机器人相关，共计10篇

【1】 A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data 标题：一种自动驾驶汽车行人检测与跟踪框架：摄像机与LiDAR数据的有效融合 链接：https://arxiv.org/abs/2108.12375

作者：Muhammad Mobaidul Islam,Abdullah Al Redwan Newaz,Ali Karimoddini 机构： Karimoddini are with theDepartment of Electrical and Computer Engineering, North Carolina A&TState University 摘要：提出了一种融合摄像机和激光雷达传感器数据的行人检测与跟踪新方法。为了应对与自主驾驶场景相关的挑战，提出了一个集成的跟踪和检测框架。检测阶段通过将激光雷达流转换为计算可处理的深度图像来执行，然后，开发深度神经网络来识别RGB和深度图像中的行人候选。为了提供准确的信息，通过使用卡尔曼滤波器融合多模态传感器信息，进一步增强了检测阶段。跟踪阶段是卡尔曼滤波预测和光流算法的组合，用于跟踪场景中的多个行人。我们在真实的公共驾驶数据集上评估我们的框架。实验结果表明，与仅使用基于图像的行人检测的基线方法相比，该方法实现了显著的性能改进。 摘要：This paper presents a novel method for pedestrian detection and tracking by fusing camera and LiDAR sensor data. To deal with the challenges associated with the autonomous driving scenarios, an integrated tracking and detection framework is proposed. The detection phase is performed by converting LiDAR streams to computationally tractable depth images, and then, a deep neural network is developed to identify pedestrian candidates both in RGB and depth images. To provide accurate information, the detection phase is further enhanced by fusing multi-modal sensor information using the Kalman filter. The tracking phase is a combination of the Kalman filter prediction and an optical flow algorithm to track multiple pedestrians in a scene. We evaluate our framework on a real public driving dataset. Experimental results demonstrate that the proposed method achieves significant performance improvement over a baseline method that solely uses image-based pedestrian detection.

【2】 Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction 标题：用于人机交互的人体行走步态建模与估计 链接：https://arxiv.org/abs/2108.12358

作者：Yash Vyas,Mike Allenspach,Christian Lanegger,Roland Siegwart,Marco Tognon 备注：To be published in The 1st AIRPHARO Workshop on Aerial Robotic Systems Physically Interacting with the Environment, 4-5/10/2021 摘要：提出了一种用于人-机器人物理交互的实时人体行走运动学建模与估计方法。根据Yoyo模型对人体在向前和垂直运动方向上的步态速度进行建模。我们设计了一种扩展卡尔曼滤波（EKF）算法来估计有偏正弦信号的频率、偏差和三角状态，从中可以提取Yoyo模型的运动学参数。基于启发式的适时滤波提高了估计的质量和鲁棒性。该方法在真实的步行人数据集上得到了成功的评估，包括复杂的轨迹和随时间变化的步长频率。 摘要：An approach to model and estimate human walking kinematics in real-time for Physical Human-Robot Interaction is presented. The human gait velocity along the forward and vertical direction of motion is modelled according to the Yoyo-model. We designed an Extended Kalman Filter (EKF) algorithm to estimate the frequency, bias and trigonometric state of a biased sinusoidal signal, from which the kinematic parameters of the Yoyo-model can be extracted. Quality and robustness of the estimation are improved by opportune filtering based on heuristics. The approach is successfully evaluated on a real dataset of walking humans, including complex trajectories and changing step frequency over time.

【3】 Lower-limb kinematics and kinetics during continuously varying human locomotion 标题：人体连续变化运动过程中下肢运动学和动力学研究 链接：https://arxiv.org/abs/2108.12307

作者：Emma Reznick,Kyle R. Embry,Ross Neuman,Edgar Bolívar-Nieto,Nicholas P. Fey,Robert D. Gregg 机构：University of Michigan, Robotics Institute, Ann Arbor, MI, USA, University of Texas at Dallas, Department of Mechanical Engineering, Richardson, TX, USA, Shirley Ryan AbilityLab, Center for Bionic Medicine, Chicago, IL, USA 摘要：人类运动涉及连续可变的活动，包括在一定速度和坡度范围内行走、跑步和爬楼梯，以及坐-站、走-跑和走-楼梯过渡。在不断变化的运动过程中，了解下肢的运动学和动力学对于开发有助于社区步行的机器人假肢和外骨骼至关重要。然而，关于人类运动的现有数据集忽略了活动之间的转换和/或这些活动期间速度和倾角的持续变化。本数据文件报告了一个新的数据集，其中包括10名健全参与者在多个斜坡（$\pm$0,5,10$^{\circ}$）和速度（0.8,1,1.2 m/s），以多种速度（1.8,2,2.2,2.4 m/s）行走和恒加速度跑步（$\pm$0.2,0.5$\text{m/s^2}$）的下肢运动学和动力学，以及具有多个楼梯坡度的楼梯上升/下降（20,25,30,35$^{\circ}$）。此数据集还包括坐立过渡、步行-跑步过渡和步行楼梯过渡。数据由维康运动捕捉系统记录，对于适用的任务，由Bertec仪器化跑步机记录。 摘要：Human locomotion involves continuously variable activities including walking, running, and stair climbing over a range of speeds and inclinations as well as sit-stand, walk-run, and walk-stairs transitions. Understanding the kinematics and kinetics of the lower limbs during continuously varying locomotion is fundamental to developing robotic prostheses and exoskeletons that assist in community ambulation. However, available datasets on human locomotion neglect transitions between activities and/or continuous variations in speed and inclination during these activities. This data paper reports a new dataset that includes the lower-limb kinematics and kinetics of ten able-bodied participants walking at multiple inclines ($\pm$ 0, 5, 10 $^{\circ}$) and speeds (0.8, 1, 1.2 m/s), running at multiple speeds (1.8, 2, 2.2, 2.4 m/s), walking and running with constant acceleration ($\pm$ 0.2, 0.5 $\text{m/s^2}$), and stair ascent/descent with multiple stair inclines (20, 25, 30, 35 $^{\circ}$). This dataset also includes sit-stand transitions, walk-run transitions, and walk-stairs transitions. Data were recorded by a Vicon motion capture system and, for applicable tasks, a Bertec instrumented treadmill.

【4】 OpenFish: Biomimetic Design of a Soft Robotic Fish for High Speed Locomotion 标题：OpenFish：高速移动软体机器鱼的仿生设计 链接：https://arxiv.org/abs/2108.12285

作者：Sander C. van den Berg,Rob B. N. Scharff,Zoltán Rusák,Jun Wu 机构：Rob B.N. Scharff∗,[,−,−,−,], Zolt´an Rus´ak,[,−,−,−,], Department of Sustainable Design Engineering, Delft University of Technology, Landbergstraat , CE, Delft, The Netherlands 备注：This paper is an extension of earlier research on a high-speed soft robotic fish. In this extension, we provide supplemental information to enable others to reproduce the soft robotic fish. We also provide additional insights in the optimization of the soft robotic fish for speed through lessons learned from previous design iterations, literature, and modeling 摘要：我们介绍OpenFish：一种开源的软机器鱼，它优化了速度和效率。这种柔软的机器鱼结合了主动和被动的尾段，精确地模拟了thunniform的游泳模式。通过实施一种新型推进系统，该系统能够以更正弦的波形实现更高的振荡频率，开源软机器鱼能够实现0.85 m/s的最高速度。因此，它比之前报道的最快的软机器鱼高出27%。除了推进系统，鱼类形态的优化在实现这一速度方面起着至关重要的作用。在这项工作中，通过对振荡推进的实验、数值和理论研究，对柔性机器鱼的优化进行了全面概述。因此，我们希望这种开源设计将加速未来软机器鱼的研究和开发。 摘要：We present OpenFish: an open source soft robotic fish which is optimized for speed and efficiency. The soft robotic fish uses a combination of an active and passive tail segment to accurately mimic the thunniform swimming mode. Through the implementation of a novel propulsion system that is capable of achieving higher oscillation frequencies with a more sinusoidal waveform, the open-source soft robotic fish was capable of achieving a top speed of 0.85 m/s. Hereby, it outperforms the previously reported fastest soft robotic fish by 27%. Besides the propulsion system, the optimization of the fish morphology played a crucial role in achieving this speed. In this work, a comprehensive overview of the optimization of the soft robotic fish through experimental, numerical and theoretical investigation into oscillating propulsion is presented. Hereby, we hope this open-source design will accelerate future research and developments in soft robotic fish.

【5】 UNICEF Guidance on AI for Children: Application to the Design of a Social Robot For and With Autistic Children 标题：联合国儿童基金会关于儿童人工智能的指导：在为自闭症儿童和与自闭症儿童一起设计社交机器人方面的应用 链接：https://arxiv.org/abs/2108.12166

作者：Séverin Lemaignan,Nigel Newbutt,Louis Rice,Joe Daly,Vicky Charisi 机构： weembedded a social robot (Softbank Pepper) in a SpecialEducational Needs (SEN) school 备注：7 pages, 3 figures, submission to the 'Achieving UN Sustainable Goals' workshop, IROS 2021 this http URL 摘要：2021年6月，在为期三周的时间里，我们在一所特殊教育需求（SEN）学校植入了一个社交机器人（软银胡椒），重点是支持自闭症儿童的福祉。我们在这些弱势群体中设计和嵌入机器人的方法遵循全面参与的方法。我们将该研究项目作为一个试验平台，在复杂的现实环境中证明儿童基金会关于儿童人工智能的九项准则的重要性和适用性。儿童基金会关于儿童人工智能的指导方针与联合国可持续发展的若干目标密切相关，因此，我们在此报告我们对这些目标的贡献。 摘要：For a period of three weeks in June 2021, we embedded a social robot (Softbank Pepper) in a Special Educational Needs (SEN) school, with a focus on supporting the well-being of autistic children. Our methodology to design and embed the robot among this vulnerable population follows a comprehensive participatory approach. We used the research project as a test-bed to demonstrate in a complex real-world environment the importance and suitability of the nine UNICEF guidelines on AI for Children. The UNICEF guidelines on AI for Children closely align with several of the UN goals for sustainable development, and, as such, we report here our contribution to these goals.

【6】 Identification of Vehicle Dynamics Parameters Using Simulation-based Inference 标题：基于仿真推理的车辆动力学参数辨识 链接：https://arxiv.org/abs/2108.12114

作者：Ali Boyali,Simon Thompson,David Robert Wong 备注：Presented at the Autoware Workshop of IEEE Intelligent Vehicle Symposium IV2021 摘要：识别轮胎和车辆参数是设计自主车辆控制和规划算法的关键步骤。本文提出了一种新的参数辨识方法：基于仿真的推理（SBI），这是对近似贝叶斯计算方法（ABC）的现代解释。基于仿真的推理是机器学习文献中的一种新兴方法，已被证明能对复杂问题中的许多参数集产生准确的结果。我们在本文中证明了它可以处理高度非线性车辆动力学参数的识别，并给出了控制方程参数的精确估计。 摘要：Identifying tire and vehicle parameters is an essential step in designing control and planning algorithms for autonomous vehicles. This paper proposes a new method: Simulation-Based Inference (SBI), a modern interpretation of Approximate Bayesian Computation methods (ABC) for parameter identification. The simulation-based inference is an emerging method in the machine learning literature and has proven to yield accurate results for many parameter sets in complex problems. We demonstrate in this paper that it can handle the identification of highly nonlinear vehicle dynamics parameters and gives accurate estimates of the parameters for the governing equations.

【7】 Predicting Stable Configurations for Semantic Placement of Novel Objects 标题：预测新对象语义放置的稳定构形 链接：https://arxiv.org/abs/2108.12062

作者：Chris Paxton,Chris Xie,Tucker Hermans,Dieter Fox 机构： Allen School of Computer Science & Engineering, USA; 3School of Computing, University of Utah 摘要：人类环境包含许多以各种安排配置的对象。我们的目标是使机器人能够在新的环境中，根据学习到的语义关系，休息以前看不见的物体。我们将这个问题分为两部分：（1）为对象找到物理上有效的位置；（2）确定这些姿势是否满足已学习的高级语义关系。我们从头开始构建模型和训练，以便与我们提出的未知对象语义放置规划算法紧密结合。我们纯粹在模拟中训练模型，不需要在现实世界中使用微调。我们的方法使运动规划成为可能，用于在具有不同几何体的场景中对未知对象进行语义重排，而仅限于RGB-D感知。我们通过一组模拟烧蚀进行的实验表明，仅使用关系分类器不足以进行可靠的规划。我们还通过对各种对象的一组真实实验，进一步证明了我们的计划者生成和执行各种操作计划的能力。 摘要：Human environments contain numerous objects configured in a variety of arrangements. Our goal is to enable robots to repose previously unseen objects according to learned semantic relationships in novel environments. We break this problem down into two parts: (1) finding physically valid locations for the objects and (2) determining if those poses satisfy learned, high-level semantic relationships. We build our models and training from the ground up to be tightly integrated with our proposed planning algorithm for semantic placement of unknown objects. We train our models purely in simulation, with no fine-tuning needed for use in the real world. Our approach enables motion planning for semantic rearrangement of unknown objects in scenes with varying geometry from only RGB-D sensing. Our experiments through a set of simulated ablations demonstrate that using a relational classifier alone is not sufficient for reliable planning. We further demonstrate the ability of our planner to generate and execute diverse manipulation plans through a set of real-world experiments with a variety of objects.

【8】 Dual-arm Coordinated Manipulation for Object Twisting with Human Intelligence 标题：利用人类智能实现物体扭曲的双臂协同操作 链接：https://arxiv.org/abs/2108.12007

作者：Weibang Bai,Ningshan Zhang,Baoru Huang,Ziwei Wang,Francesco Cursi,Ya-Yen Tsai,Bo Xiao,Eric Yeatman 备注：Accepted by IEEE SMC 2021, 7 pages, 7 figures 摘要：机器人双臂扭转在工业生产和日常服务中都是一项常见但极具挑战性的任务，因为它通常需要灵巧的协作、大规模的末端执行器旋转以及良好的对象操纵适应性。同时，安全性和效率是机器人双臂协调操作的首要问题。因此，通常采用的基于环境感知和运动规划技术的全自动任务执行方法对于艰巨的扭曲任务仍然是不足和有问题的。为此，本文提出了一种新颖的双臂协调控制策略，该策略基于一只手臂的优化运动规划和另一只手臂的实时遥控与人类智能相结合。分析和仿真结果表明，该方法能够实现双臂无碰撞、无奇异，提高了灵巧性、安全性和效率。 摘要：Robotic dual-arm twisting is a common but very challenging task in both industrial production and daily services, as it often requires dexterous collaboration, a large scale of end-effector rotating, and good adaptivity for object manipulation. Meanwhile, safety and efficiency are preliminary concerns for robotic dual-arm coordinated manipulation. Thus, the normally adopted fully automated task execution approaches based on environmental perception and motion planning techniques are still inadequate and problematic for the arduous twisting tasks. To this end, this paper presents a novel strategy of the dual-arm coordinated control for twisting manipulation based on the combination of optimized motion planning for one arm and real-time telecontrol with human intelligence for the other. The analysis and simulation results showed it can achieve collision and singularity free for dual arms with enhanced dexterity, safety, and efficiency.

【9】 Robust Motion Planning in the Presence of Estimation Uncertainty 标题：估计不确定条件下的鲁棒运动规划 链接：https://arxiv.org/abs/2108.11983

作者：Lars Lindemann,Matthew Cleaveland,Yiannis Kantaros,George J. Pappas 机构：Department of Electrical and Systems Engineering, University of Pennsylvania 备注：Accepted at the Conference on Decision and Control 2021 摘要：运动规划是一个基本问题，重点是寻找控制输入，使机器人能够到达目标区域，同时安全地避开障碍物。然而，在许多情况下，系统的状态可能未知，而仅使用例如卡尔曼滤波器来估计。这导致了一个新的运动规划问题，在存在状态估计不确定性的情况下，必须确保安全性。以前解决这个问题的方法要么是保守的，要么是乐观地集成状态估计，这会导致非稳健解。乐观的解决方案需要频繁地重新规划，以避免危及系统的安全。我们提出了一个新的公式来解决这个问题，目的是在不过度保守的情况下对状态估计误差具有鲁棒性。特别地，我们提出了一个随机最优控制问题，该问题包含鲁棒的风险感知安全约束，通过引入鲁棒裕度来考虑状态估计误差。我们提出了一种新的基于采样的方法，该方法通过构建树来探索高斯分布的可达空间，从而捕获状态估计和未来测量中的不确定性。我们提供了稳健性保证，并在理论和仿真中表明，诱导的稳健性裕度构成了保守性和稳健性之间的折衷，用于在允许控制重新规划频率的估计不确定性下进行规划。 摘要：Motion planning is a fundamental problem and focuses on finding control inputs that enable a robot to reach a goal region while safely avoiding obstacles. However, in many situations, the state of the system may not be known but only estimated using, for instance, a Kalman filter. This results in a novel motion planning problem where safety must be ensured in the presence of state estimation uncertainty. Previous approaches to this problem are either conservative or integrate state estimates optimistically which leads to non-robust solutions. Optimistic solutions require frequent replanning to not endanger the safety of the system. We propose a new formulation to this problem with the aim to be robust to state estimation errors while not being overly conservative. In particular, we formulate a stochastic optimal control problem that contains robustified risk-aware safety constraints by incorporating robustness margins to account for state estimation errors. We propose a novel sampling-based approach that builds trees exploring the reachable space of Gaussian distributions that capture uncertainty both in state estimation and in future measurements. We provide robustness guarantees and show, both in theory and simulations, that the induced robustness margins constitute a trade-off between conservatism and robustness for planning under estimation uncertainty that allows to control the frequency of replanning.

【10】 MRI-compatible electromagnetic servomotors for image-guided robotic procedures 标题：用于图像引导机器人手术的与MRI兼容的电磁伺服马达 链接：https://arxiv.org/abs/2108.12266

作者：Lorne W. Hofstetter,Rock Hadley,Robb Merrill,Huy Pham,Gabriel C. Fine,Dennis L. Parker 机构：Parker, Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA 备注：20 pages, 5 figures, 1 table 摘要：将磁共振成像（MRI）无与伦比的软组织成像能力与高精度机器人技术相结合，有可能提高各种图像引导医疗程序的准确性、精确度和安全性。然而，高功能MRI兼容机器人系统的目标尚未实现，因为医疗机器人使用的传统电磁伺服电机可能在MRI扫描仪的强磁场附近成为危险的弹丸。在这里，我们报告了一种新型的电磁伺服电机设计，它由非磁性部件构成，可以在临床扫描仪的患者区域内工作。我们表明，这种设计能够在成像期间实现高扭矩和精确控制的旋转驱动。利用该伺服电机设计，构建并测试了一个与MRI兼容的机器人。该机器人演示了在组织中操作大直径手术器械所需的线性力可以在与MRI同时成像的过程中实现。这项工作提出了第一个全功能的电磁伺服电机，可以在3特斯拉临床MRI扫描仪的患者区域安全操作（成像）。 摘要：Combining the unmatched soft-tissue imaging capabilities of magnetic resonance imaging (MRI) with high precision robotics has the potential to improve the accuracy, precision, and safety of a wide range of image-guided medical procedures. However, the goal of highly functional MRI-compatible robotic systems has not yet been realized because conventional electromagnetic servomotors used by medical robots can become dangerous projectiles near the strong magnetic field of an MRI scanner. Here we report a novel electromagnetic servomotor design that is constructed from non-magnetic components and can operate within the patient area of clinical scanners. We show that this design enables high-torque and precisely controlled rotary actuation during imaging. Using this servomotor design, an MRI-compatible robot was constructed and tested. The robot demonstrated that the linear forces required to manipulate large diameter surgical instruments in tissues could be achieved during simultaneous imaging with MRI. This work presents the first fully functional electromagnetic servomotor that can be safely operated (while imaging) in the patient area of a 3 Tesla clinical MRI scanner.

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