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International Journal of Robotics Research最新文献

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Robotics Research 机器人研究
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-25555-7
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引用次数: 9
Alternating direction method of multipliers-based distributed control for distributed manipulation by shaping physical force fields 基于乘法器的物理力场成形分布式操作交替方向控制方法
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2023-01-01 DOI: 10.1177/02783649231153958
Martin Gurtner, J. Zemánek, Z. Hurák
This paper proposes an algorithm for decomposing and possibly distributing an optimization problem that naturally emerges in distributed manipulation by shaping physical force fields through actuators distributed in space (arrays of actuators). One or several manipulated objects located in this field can “feel the force” and move simultaneously and independently. The control system has to produce commands for all actuators so that desired forces are developed at several prescribed places. This can be formulated as an optimization problem that has to be solved in every sampling period. Exploiting the structure of the optimization problem is crucial for platforms with many actuators and many manipulated objects, hence the goal of decomposing the huge optimization problem into several subproblems. Furthermore, if the platform is composed of interconnected actuator modules with computational capabilities, the decomposition can give guidance for the distribution of the computation to the modules. We propose an algorithm for decomposing/distributing the optimization problem using Alternating Direction Method of Multipliers (ADMM). The proposed algorithm is shown to converge to modest accuracy for various distributed platforms in a few iterations. We demonstrate our algorithm through numerical experiments corresponding to three physical experimental platforms for distributed manipulation using electric, magnetic, and pressure fields. Furthermore, we deploy and test it on real experimental platforms for distributed manipulation using an array of solenoids and ultrasonic transducers.
本文提出了一种算法,通过分布在空间中的执行器(执行器阵列)塑造物理力场,对分布式操作中自然出现的优化问题进行分解和可能分布。位于该场中的一个或几个被操纵的物体可以“感受到力”并同时独立地移动。控制系统必须对所有执行器发出指令,以便在几个规定的地方产生所需的力。这可以被表述为必须在每个采样周期内解决的优化问题。对于具有多个执行机构和多个被操纵对象的平台,利用优化问题的结构是至关重要的,因此目标是将庞大的优化问题分解为几个子问题。此外,如果平台由具有计算能力的相互连接的执行器模块组成,则分解可以指导计算分配到模块上。提出了一种利用乘法器交替方向法(ADMM)分解/分配优化问题的算法。结果表明,该算法在不同的分布式平台上迭代次数少,收敛精度适中。我们通过与三个物理实验平台相对应的数值实验来证明我们的算法,这些实验平台使用电场、磁场和压力场进行分布式操作。此外,我们在真实的实验平台上部署和测试它,使用一系列螺线管和超声波换能器进行分布式操作。
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引用次数: 1
Impact of colchicine on mortality and morbidity in COVID-19: a systematic review. COVID-19中秋水仙碱对死亡率和发病率的影响:系统综述。
IF 4.9 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-12-01 DOI: 10.1080/07853890.2021.1993327
Devang Sanghavi, Pankaj Bansal, Ikwinder Preet Kaur, Mohsin Sheraz Mughal, Chandana Keshavamurthy, Austin Cusick, Jennifer Schram, Siva Naga S Yarrarapu, Abhishek R Giri, Nirmaljot Kaur, Pablo Moreno Franco, Andy Abril, Fawad Aslam

Introduction: Colchicine, because of its anti-inflammatory and possible anti-viral properties, has been proposed as potential therapeutic option for COVID-19. The role of colchicine to mitigate "cytokine storm" and to decrease the severity and mortality associated with COVID-19 has been evaluated in many studies.

Objective: To evaluate the role of colchicine on morbidity and mortality in COVID-19 patients.

Methods: This systematic review was conducted in accordance with the PRISMA recommendations. The literature search was conducted in 6 medical databases from inception to February 17, 2021 to identify studies evaluating colchicine as a therapeutic agent in COVID-19. All included studies were evaluated for risk of bias (ROB) using the Revised Cochrane ROB tool for randomised controlled trials (RCTs) and Newcastle-Ottawa Scale (NOS) for case-control and cohort studies.

Results: Four RCTs and four observational studies were included in the final analysis. One study evaluated colchicine in outpatients, while all others evaluated inpatient use of colchicine. There was significant variability in treatment protocols for colchicine and standard of care in all studies. A statistically significant decrease in all-cause mortality was observed in three observational studies. The risk of mechanical ventilation was significantly reduced only in one observational study. Length of hospitalisation was significantly reduced in two RCTs. Risk for hospitalisation was not significantly decreased in the study evaluating colchicine in outpatients. Very few studies had low risk of bias.

Conclusion: Based on the available data, colchicine shall not be recommended to treat COVID-19. Further high-quality and multi-center RCTs are required to assess the meaningful impact of this drug in COVID-19.KEY MESSAGESColchicine, an anti-inflammatory agent has demonstrated anti-viral properties in in-vitro studies by degrading the microtubules, as well as by inhibiting the production of pro-inflammatory cytokines.Colchicine has been studied as a potential therapeutic option for COVID-19, with variable results.Until further research can establish the efficacy of colchicine in COVID-19, the use of colchicine in COVID-19 shall be restricted to clinical trials.

简介秋水仙碱具有抗炎和可能抗病毒的特性,因此被认为是COVID-19的潜在治疗方案。许多研究都评估了秋水仙碱在减轻 "细胞因子风暴"、降低 COVID-19 的严重程度和死亡率方面的作用:评估秋水仙碱对COVID-19患者发病率和死亡率的作用:本系统性综述根据 PRISMA 建议进行。从开始到 2021 年 2 月 17 日,在 6 个医学数据库中进行了文献检索,以确定将秋水仙碱作为 COVID-19 治疗药物的评估研究。所有纳入的研究均采用修订版 Cochrane ROB 工具对随机对照试验(RCT)进行了偏倚风险(ROB)评估,并采用纽卡斯尔-渥太华量表(NOS)对病例对照和队列研究进行了偏倚风险评估:最终分析纳入了四项随机对照试验和四项观察性研究。其中一项研究评估了门诊患者使用秋水仙碱的情况,而其他所有研究都评估了住院患者使用秋水仙碱的情况。在所有研究中,秋水仙碱的治疗方案与标准护理方案存在很大差异。三项观察性研究发现,全因死亡率在统计学上有明显下降。只有一项观察性研究显著降低了机械通气的风险。在两项研究中,住院时间明显缩短。在评估门诊患者使用秋水仙碱的研究中,住院风险并未明显降低。极少数研究的偏倚风险较低:根据现有数据,不推荐使用秋水仙碱治疗 COVID-19。关键信息:秋水仙碱是一种抗炎药物,通过降解微管和抑制促炎细胞因子的产生,在体外研究中表现出抗病毒特性。在进一步研究确定秋水仙碱对 COVID-19 的疗效之前,秋水仙碱对 COVID-19 的使用应仅限于临床试验。
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引用次数: 0
Continuum robot state estimation using Gaussian process regression on S E ( 3 ) 基于SE(3)的高斯过程回归连续体机器人状态估计
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-10-21 DOI: 10.1177/02783649221128843
S. Lilge, T. Barfoot, J. Burgner-Kahrs
Continuum robots have the potential to enable new applications in medicine, inspection, and countless other areas due to their unique shape, compliance, and size. Excellent progress has been made in the mechanical design and dynamic modeling of continuum robots, to the point that there are some canonical designs, although new concepts continue to be explored. In this paper, we turn to the problem of state estimation for continuum robots that can been modeled with the common Cosserat rod model. Sensing for continuum robots might comprise external camera observations, embedded tracking coils, or strain gauges. We repurpose a Gaussian process (GP) regression approach to state estimation, initially developed for continuous-time trajectory estimation in SE(3). In our case, the continuous variable is not time but arclength and we show how to estimate the continuous shape (and strain) of the robot (along with associated uncertainties) given discrete, noisy measurements of both pose and strain along the length. We demonstrate our approach quantitatively through simulations as well as through experiments. Our evaluations show that accurate and continuous estimates of a continuum robot’s shape can be achieved, resulting in average end-effector errors between the estimated and ground truth shape as low as 3.5 mm and 0.016° in simulation or 3.3 mm and 0.035° for unloaded configurations and 6.2 mm and 0.041° for loaded ones during experiments, when using discrete pose measurements.
连续体机器人由于其独特的形状、顺应性和尺寸,有可能在医学、检查和无数其他领域实现新的应用。连续体机器人的机械设计和动力学建模已经取得了卓越的进展,尽管新的概念仍在探索中,但已经有了一些规范的设计。在本文中,我们转向连续机器人的状态估计问题,该问题可以用通用的Cosserat杆模型建模。连续体机器人的传感可能包括外部摄像机观测、嵌入式跟踪线圈或应变仪。我们将高斯过程(GP)回归方法重新用于状态估计,该方法最初是为SE(3)中的连续时间轨迹估计而开发的。在我们的情况下,连续变量不是时间,而是弧长,我们展示了如何在给定沿长度的姿态和应变的离散、有噪声测量的情况下估计机器人的连续形状(和应变)(以及相关的不确定性)。我们通过模拟和实验定量地展示了我们的方法。我们的评估表明,当使用离散姿态测量时,可以实现对连续机器人形状的精确和连续估计,从而在模拟中,估计的形状与真实形状之间的平均末端执行器误差低至3.5 mm和0.016°,在实验中,无载配置的末端执行器平均误差低至3.3 mm和0.035°,加载配置的末端执行者平均误差低为6.2 mm和0.041°。
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引用次数: 9
Constraint-consistent task-oriented whole-body robot formulation: Task, posture, constraints, multiple contacts, and balance 约束一致的面向任务的全身机器人公式:任务、姿势、约束、多触点和平衡
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-10-02 DOI: 10.1177/02783649221120029
O. Khatib, Mikael Jorda, Jaeheung Park, L. Sentis, S. Chung
We present a comprehensive formulation to the problem of controlling a high-dimensional robotic system involving complex tasks subject to a variety of constraints, obstacles, balance, and contact challenges. Using intuitive and natural representations, the approach is initiated by establishing individual objectives for a task and its constraints. Simple independent controllers using artificial potential fields are then designed for each objective to reach goals while enforcing the constraints. Dynamically consistent projections in nullspaces associated with task and constraint representations are employed to deliver a coherent whole-body robot control. In multi-link multi-contact tasks, contact forces produce both resulting and internal forces. Internal forces play a critical role in robot balance and stability, achieved in this framework through modeling and controlling virtual linkages that explicitly describe the relationship between active/passive contact force, resultant force, controlled/uncontrolled internal force for multi-link multi-contact underactuated robots. Control of contacts with the environment involves material considerations such as friction and geometric constraints. Potential barriers direct the selection of contact forces ensuring stability and balance. This approach of dynamic projection and the Virtual Linkage Model addresses robot underactuation. In addition, the framework introduces a coordinate completion mechanism to establish a generalized coordinates representation of the task, removing redundancy and maintaining the full operational space dynamics description. This enables task-space dynamic control based on the relevant inertial properties. We present the experimental validation on a physical humanoid platform.
我们对高维机器人系统的控制问题提出了一个全面的公式,该系统涉及受各种约束、障碍、平衡和接触挑战的复杂任务。该方法使用直观和自然的表示,通过为任务及其约束建立个人目标来启动。然后为每个目标设计使用人工势场的简单独立控制器,以在实施约束的同时达到目标。采用与任务和约束表示相关联的零空间中的动态一致投影来提供连贯的全身机器人控制。在多环节多接触任务中,接触力产生合力和内力。内力在机器人的平衡和稳定性中起着关键作用,在该框架中,通过建模和控制虚拟连杆来实现,这些虚拟连杆明确描述了多连杆多接触欠驱动机器人的主动/被动接触力、合力、受控/非受控内力之间的关系。控制与环境的接触涉及材料因素,如摩擦和几何约束。潜在的障碍物指导接触力的选择,确保稳定性和平衡性。这种动态投影和虚拟连杆模型的方法解决了机器人的欠驱动问题。此外,该框架引入了坐标完成机制,以建立任务的广义坐标表示,消除冗余并保持完整的操作空间动力学描述。这使得能够基于相关惯性特性进行任务空间动态控制。我们在一个物理类人平台上进行了实验验证。
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引用次数: 0
MassMIND: Massachusetts Maritime INfrared Dataset MassMIND:马萨诸塞州海事红外数据集
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-09-09 DOI: 10.1177/02783649231153020
Shailesh Nirgudkar, M. Defilippo, Michael Sacarny, M. Benjamin, P. Robinette
Recent advances in deep learning technology have triggered radical progress in the autonomy of ground vehicles. Marine coastal Autonomous Surface Vehicles (ASVs) that are regularly used for surveillance, monitoring, and other routine tasks can benefit from this autonomy. Long haul deep sea transportation activities are additional opportunities. These two use cases present very different terrains—the first being coastal waters—with many obstacles, structures, and human presence while the latter is mostly devoid of such obstacles. Variations in environmental conditions are common to both terrains. Robust labeled datasets mapping such terrains are crucial in improving the situational awareness that can drive autonomy. However, there are only limited such maritime datasets available and these primarily consist of optical images. Although, long wave infrared (LWIR) is a strong complement to the optical spectrum that helps in extreme light conditions, a labeled public dataset with LWIR images does not currently exist. In this paper, we fill this gap by presenting a labeled dataset of over 2900 LWIR segmented images captured in coastal maritime environment over a period of 2 years. The images are labeled using instance segmentation and classified into seven categories—sky, water, obstacle, living obstacle, bridge, self, and background. We also evaluate this dataset across three deep learning architectures (UNet, PSPNet, DeepLabv3) and provide detailed analysis of its efficacy. While the dataset focuses on the coastal terrain, it can equally help deep sea use cases. Such terrain would have less traffic, and the classifier trained on cluttered environment would be able to handle sparse scenes effectively. We share this dataset with the research community with the hope that it spurs new scene understanding capabilities in the maritime environment.
深度学习技术的最新进展已经在地面车辆的自动驾驶方面取得了突破性进展。经常用于监视、监测和其他日常任务的沿海自主水面车辆(asv)可以从这种自主性中受益。长途深海运输活动是额外的机会。这两个用例呈现了非常不同的地形——第一个是沿海水域——有许多障碍物、结构和人类的存在,而后者基本上没有这些障碍。环境条件的变化对这两个地区来说都是共同的。绘制此类地形的稳健标记数据集对于提高能够驱动自动驾驶的态势感知至关重要。然而,只有有限的海洋数据集,这些数据集主要由光学图像组成。尽管长波红外(LWIR)是光谱的强大补充,有助于在极端光照条件下,但目前还不存在带有长波红外图像的标记公共数据集。在本文中,我们通过提供在沿海海洋环境中捕获的超过2900幅LWIR分割图像的标记数据集来填补这一空白。使用实例分割对图像进行标记,并将图像分为天空、水、障碍物、活障碍物、桥梁、自我和背景7类。我们还跨三种深度学习架构(UNet, PSPNet, DeepLabv3)评估了该数据集,并提供了其有效性的详细分析。虽然数据集侧重于沿海地形,但它同样可以帮助深海用例。这样的地形会有更少的流量,并且在混乱环境下训练的分类器能够有效地处理稀疏的场景。我们与研究界分享这个数据集,希望它能在海洋环境中激发新的场景理解能力。
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引用次数: 3
Passive and active acoustic sensing for soft pneumatic actuators 软气动执行器的被动和主动声学传感
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-08-22 DOI: 10.1177/02783649231168954
Vincent Wall, Gabriel Zöller, O. Brock
We propose a sensorization method for soft pneumatic actuators that uses an embedded microphone and speaker to measure different actuator properties. The physical state of the actuator determines the specific modulation of sound as it travels through the structure. Using simple machine learning, we create a computational sensor that infers the corresponding state from sound recordings. We demonstrate the acoustic sensor on a soft pneumatic continuum actuator and use it to measure contact locations, contact forces, object materials, actuator inflation, and actuator temperature. We show that the sensor is reliable (average classification rate for six contact locations of 93%), precise (mean spatial accuracy of 3.7 mm), and robust against common disturbances like background noise. Finally, we compare different sounds and learning methods and achieve best results with 20 ms of white noise and a support vector classifier as the sensor model.
我们提出了一种软气动执行器的传感方法,该方法使用嵌入式麦克风和扬声器来测量执行器的不同特性。执行器的物理状态决定了声音在结构中传播时的特定调制。使用简单的机器学习,我们创建了一个计算传感器,从录音中推断出相应的状态。我们演示了软气动连续执行器上的声学传感器,并用它来测量接触位置、接触力、物体材料、执行器膨胀和执行器温度。我们表明,该传感器可靠(六个接触位置的平均分类率为93%),精确(平均空间精度为3.7 mm),并且对背景噪声等常见干扰具有鲁棒性。最后,我们比较了不同的声音和学习方法,并以20 ms白噪声和支持向量分类器作为传感器模型获得了最好的结果。
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引用次数: 7
Versatile articulated aerial robot DRAGON: Aerial manipulation and grasping by vectorable thrust control 多用途铰接式空中机器人龙:空中操纵和抓取矢量推力控制
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-08-18 DOI: 10.1177/02783649221112446
Moju Zhao, K. Okada, M. Inaba
Various state-of-the-art works have achieved aerial manipulation and grasping by attaching additional manipulator to aerial robots. However, such a coupled platform has limitations with respect to the interaction force and mobility. In this paper, we present the successful implementation of aerial manipulation and grasping by a novel articulated aerial robot called DRAGON, in which a vectorable rotor unit is embedded in each link. The key to performing stable manipulation and grasping in the air is the usage of rotor vectoring apparatus having two degrees-of-freedom. First, a comprehensive flight control methodology for aerial transformation using the vectorable thrust force is developed with the consideration of the dynamics of vectoring actuators. This proposed control method can suppress the oscillation due to the dynamics of vectoring actuators and also allow the integration with external and internal wrenches for object manipulation and grasping. Second, an online thrust-level planning method for bimanual object grasping using the two ends of this articulated model is presented. The proposed grasping style is unique in that the vectorable thrust force is used as the internal wrench instead of the joint torque. Finally, we show the experimental results of evaluation on the proposed control and planning methods for object manipulation and grasping.
各种最新的研究成果通过在空中机器人上附加机械臂来实现空中操纵和抓取。然而,这种耦合平台在相互作用力和机动性方面存在局限性。在本文中,我们提出了一种新型铰接式空中机器人DRAGON的成功实现空中操纵和抓取,其中每个环节都嵌入了一个矢量转子单元。二自由度转子矢量装置的使用是实现稳定操纵和抓握的关键。首先,考虑矢量作动器的动力学特性,提出了一种基于矢量推力的空中变换综合飞行控制方法。所提出的控制方法可以抑制矢量执行器的动力学振荡,并允许与外部和内部扳手集成以实现物体的操作和抓取。其次,利用该铰接模型的两端,提出了一种手动抓取物体的在线推力级规划方法。所提出的抓取方式的独特之处在于,矢量推力被用作内部扳手而不是关节扭矩。最后,给出了对所提出的物体操纵和抓取控制和规划方法的实验评价结果。
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引用次数: 9
Method for generating real-time interactive virtual fixture for shared teleoperation in unknown environments 未知环境下共享遥操作实时交互式虚拟夹具的生成方法
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-08-01 DOI: 10.1177/02783649221102980
Vitalii Pruks, J. Ryu
A virtual fixture (VF) is a constraint built into software that assists a human operator in moving a remote tool along a preferred path via an augmented guidance force to improve teleoperation performance. However, teleoperation generally applies to unknown or dynamic environments, which are challenging for VF use. Most researchers have assumed that VFs are pre-defined or generated automatically; however, these processes are complicated and unreliable in unknown environments where teleoperation is in high demand. Recently, a few researchers have addressed this issue by introducing a user-interactive method of generating VFs in unknown environments. However, these methods are limited to generating a single type of primitive for a single robot tool. Moreover, the accuracy of the VF generated by these methods depends on the accuracy of the human input. Thus, applications of these methods are limited. To overcome those limitations, this work introduces a novel interactive VF generation method that includes a new method of representing VFs as a composition of components. A feature-based user interface allows the human operator to intuitively specify the VF components. The new VF representation accommodates a variety of robot tools and actions. Using the feature-based interface, the process of VF generation is more intuitive and accurate. In this study, the proposed method is evaluated with human subjects in three teleoperation experiments: peg-in-hole, pipe-sawing, and pipe-welding. The experimental results show that the VFs generated by the proposed approach result in a higher manipulation quality while demonstrating the lowest total workload in all experiments. The peg-in-hole task teleoperation was the safest in terms of failure proportion and exerted force of the robot tool. In the pipe-sawing task, the positioning of the robot tool was the most accurate. In the pipe-welding task, the quality of weld was the best in terms of measured tool-trajectory smoothness and visual weld observation.
虚拟夹具(VF)是一种内置在软件中的约束,它通过增强的引导力帮助操作员沿着首选路径移动远程工具,以提高远程操作性能。然而,远程操作通常适用于未知或动态环境,这对VF的使用具有挑战性。大多数研究人员都认为VFs是预先定义的或自动生成的;然而,这些过程在对远程操作有很高要求的未知环境中是复杂和不可靠的。最近,一些研究人员通过引入在未知环境中生成vf的用户交互方法来解决这个问题。然而,这些方法仅限于为单个机器人工具生成单一类型的原语。此外,这些方法生成的VF的准确性取决于人工输入的准确性。因此,这些方法的应用是有限的。为了克服这些限制,本工作引入了一种新的交互式VF生成方法,其中包括一种将VF表示为组件组合的新方法。基于特征的用户界面允许操作员直观地指定VF组件。新的VF表示适应各种机器人工具和动作。采用基于特征的界面,使VF生成过程更加直观、准确。在本研究中,我们以人体为实验对象,进行了三种远程操作实验:钉孔、管材锯切和管材焊接。实验结果表明,该方法生成的VFs具有较高的操作质量,并且在所有实验中显示出最低的总工作量。在机器人刀具的失效比例和受力方面,钉孔任务遥操作是最安全的。在管材锯切任务中,机器人刀具的定位是最准确的。在管焊作业中,从测量的刀具轨迹光洁度和焊缝视觉观察两方面来看,焊缝质量最好。
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引用次数: 7
Offline motion libraries and online MPC for advanced mobility skills 离线动作库和在线MPC提供高级移动技能
IF 9.2 1区 计算机科学 Q1 ROBOTICS Pub Date : 2022-08-01 DOI: 10.1177/02783649221102473
Marko Bjelonic, R. Grandia, Moritz Geilinger, Oliver Harley, V. S. Medeiros, Vuk Pajovic, E. Jelavic, Stelian Coros, M. Hutter
We describe an optimization-based framework to perform complex locomotion skills for robots with legs and wheels. The generation of complex motions over a long-time horizon often requires offline computation due to current computing constraints and is mostly accomplished through trajectory optimization (TO). In contrast, model predictive control (MPC) focuses on the online computation of trajectories, robust even in the presence of uncertainty, albeit mostly over shorter time horizons and is prone to generating nonoptimal solutions over the horizon of the task’s goals. Our article’s contributions overcome this trade-off by combining offline motion libraries and online MPC, uniting a complex, long-time horizon plan with reactive, short-time horizon solutions. We start from offline trajectories that can be, for example, generated by TO or sampling-based methods. Also, multiple offline trajectories can be composed out of a motion library into a single maneuver. We then use these offline trajectories as the cost for the online MPC, allowing us to smoothly blend between multiple composed motions even in the presence of discontinuous transitions. The MPC optimizes from the measured state, resulting in feedback control, which robustifies the task’s execution by reacting to disturbances and looking ahead at the offline trajectory. With our contribution, motion designers can choose their favorite method to iterate over behavior designs offline without tuning robot experiments, enabling them to author new behaviors rapidly. Our experiments demonstrate complex and dynamic motions on our traditional quadrupedal robot ANYmal and its roller-walking version. Moreover, the article’s findings contribute to evaluating five planning algorithms.
我们描述了一个基于优化的框架,用于为有腿和轮子的机器人执行复杂的运动技能。由于当前的计算限制,在长时间范围内生成复杂运动通常需要离线计算,并且主要通过轨迹优化(to)来实现。相比之下,模型预测控制(MPC)专注于轨迹的在线计算,即使在存在不确定性的情况下也具有鲁棒性,尽管大多在较短的时间范围内,并且容易在任务目标范围内生成非最优解。我们的文章通过将离线运动库和在线MPC相结合,将复杂的长期计划与反应性的短期解决方案相结合,克服了这种权衡。我们从离线轨迹开始,例如,可以通过TO或基于采样的方法生成。此外,多个离线轨迹可以从一个运动库组成一个单独的机动。然后,我们使用这些离线轨迹作为在线MPC的成本,使我们能够在多个合成运动之间平滑地混合,即使存在不连续的过渡。MPC根据测量状态进行优化,从而产生反馈控制,通过对干扰做出反应并展望离线轨迹来稳健地执行任务。有了我们的贡献,运动设计师可以选择他们最喜欢的方法离线迭代行为设计,而无需调整机器人实验,使他们能够快速创建新的行为。我们的实验在传统的四足机器人ANYmal及其滚轮行走版本上演示了复杂的动态运动。此外,文章的发现有助于评估五种规划算法。
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引用次数: 18
期刊
International Journal of Robotics Research
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