机器人相关学术速递[7.26]

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cs.RO机器人相关，共计19篇

【1】 Provident Vehicle Detection at Night for Advanced Driver Assistance Systems 标题：高级驾驶员辅助系统的夜间防盗车辆检测

作者：Lukas Ewecker,Ebubekir Asan,Lars Ohnemus,Sascha Saralajew 机构：the date of receipt and acceptance should be inserted later 链接：https://arxiv.org/abs/2107.11302 摘要：近年来，计算机视觉算法越来越强大，使得自动驾驶等技术得以快速发展。然而，目前的算法主要有一个局限性：它们依赖于直接可见的对象。这是与人类行为相比的一个主要缺点，在人类行为中，由实际对象（例如阴影）引起的间接视觉线索已经被直观地用于检索信息或预测发生的对象。在夜间驾驶时，这种性能缺陷变得更加明显：人类已经处理迎面而来的车辆造成的光伪影，以假设其未来的外观，而当前的目标检测系统依赖于迎面而来的车辆的直接可见性。在本课题前期工作的基础上，本文提出了一个完整的系统，该系统能够解决在夜间根据迎面而来的车辆所引起的光伪影来检测迎面而来的车辆的任务。为此，我们概述了完整的算法体系结构，包括图像空间中的光伪影检测、三维空间中的目标定位以及随时间推移的目标验证。为了验证该系统的适用性，我们将该系统部署在一辆测试车上，并利用预先检测到的车辆信息主动控制无眩光远光灯系统。利用这个实验设置，我们量化的时间效益，公积金车辆检测系统提供了一个生产中的计算机视觉系统相比。此外，无眩光远光用例提供了检测结果的实时和真实可视化界面。有了这一贡献，我们希望将注意力放在非常规的感知任务上，即预先目标检测，并进一步缩小人类行为与计算机视觉算法之间的性能差距，从而使自动驾驶向前迈进一步。 摘要：In recent years, computer vision algorithms have become more and more powerful, which enabled technologies such as autonomous driving to evolve with rapid pace. However, current algorithms mainly share one limitation: They rely on directly visible objects. This is a major drawback compared to human behavior, where indirect visual cues caused by the actual object (e.g., shadows) are already used intuitively to retrieve information or anticipate occurring objects. While driving at night, this performance deficit becomes even more obvious: Humans already process the light artifacts caused by oncoming vehicles to assume their future appearance, whereas current object detection systems rely on the oncoming vehicle's direct visibility. Based on previous work in this subject, we present with this paper a complete system capable of solving the task to providently detect oncoming vehicles at nighttime based on their caused light artifacts. For that, we outline the full algorithm architecture ranging from the detection of light artifacts in the image space, localizing the objects in the three-dimensional space, and verifying the objects over time. To demonstrate the applicability, we deploy the system in a test vehicle and use the information of providently detected vehicles to control the glare-free high beam system proactively. Using this experimental setting, we quantify the time benefit that the provident vehicle detection system provides compared to an in-production computer vision system. Additionally, the glare-free high beam use case provides a real-time and real-world visualization interface of the detection results. With this contribution, we want to put awareness on the unconventional sensing task of provident object detection and further close the performance gap between human behavior and computer vision algorithms in order to bring autonomous and automated driving a step forward.

【2】 DronePaint: Swarm Light Painting with DNN-based Gesture Recognition 标题：DronePaint：基于DNN的手势识别群光绘画

作者：Valerii Serpiva,Ekaterina Karmanova,Aleksey Fedoseev,Stepan Perminov,Dzmitry Tsetserukou 机构：Skolkovo Institute of Science and, Technology, Moscow, Russia 备注：ACM SIGGRAPH 21. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. arXiv admin note: substantial text overlap with arXiv:2106.14698 链接：https://arxiv.org/abs/2107.11288 摘要：提出了一种新的基于DNN的手势识别的人机交互系统，允许用户在复杂环境中通过手势界面绘制轨迹，直接控制一群无人机。开发的基于CV的系统允许用户在不需要额外设备的情况下，通过人类的手势和动作实时控制群体的行为，为改变群体的形状和队形提供了方便的工具。提出并实现了两种交互方式来调整群体层次结构：轨迹绘制和自由形式轨迹生成控制。实验结果表明，手势识别系统具有较高的准确率（99.75%），允许用户在三种评估轨迹模式上获得相对较高的轨迹绘制精度（平均误差为5.6cm，而鼠标绘制的平均误差为3.1cm）。该系统可应用于复杂环境探测、无人机喷绘、无人机互动表演等领域，用户可以通过无人机群来创作自己的艺术作品。 摘要：We propose a novel human-swarm interaction system, allowing the user to directly control a swarm of drones in a complex environment through trajectory drawing with a hand gesture interface based on the DNN-based gesture recognition. The developed CV-based system allows the user to control the swarm behavior without additional devices through human gestures and motions in real-time, providing convenient tools to change the swarm's shape and formation. The two types of interaction were proposed and implemented to adjust the swarm hierarchy: trajectory drawing and free-form trajectory generation control. The experimental results revealed a high accuracy of the gesture recognition system (99.75%), allowing the user to achieve relatively high precision of the trajectory drawing (mean error of 5.6 cm in comparison to 3.1 cm by mouse drawing) over the three evaluated trajectory patterns. The proposed system can be potentially applied in complex environment exploration, spray painting using drones, and interactive drone shows, allowing users to create their own art objects by drone swarms.

【3】 An Improved Algorithm of Robot Path Planning in Complex Environment Based on Double DQN 标题：基于双DQN的复杂环境下机器人路径规划改进算法

作者：Fei Zhang,Chaochen Gu,Feng Yang 机构： Shanghai Jiao Tong University, Shanghai, China, Northwestern Polytechnical University, ShaanXi, China 备注：Accepted in International Conference on Guidance, Navigation and Control,2020 链接：https://arxiv.org/abs/2107.11245 摘要：实验结果表明，Deep-Q网络（DQN）在具有多种困境的环境中进行路径规划时存在一定的局限性。奖励函数可能很难建模，成功的经验转换很难在经验回放中找到。在这种背景下，本文提出了一种改进的双DQN（DDQN）算法来解决这一问题。为了实现丰富的经验回放实验，基于RRT策略重新定义了每轮训练中机器人的初始化。此外，根据A*中职位成本的定义，专门设计了免费职位奖励，以加速学习过程。仿真实验结果验证了改进的DDQN算法的有效性，机器人能够成功地学习DQN和DDQN对机器人避障和最优路径规划的影响。 摘要：Deep Q Network (DQN) has several limitations when applied in planning a path in environment with a number of dilemmas according to our experiment. The reward function may be hard to model, and successful experience transitions are difficult to find in experience replay. In this context, this paper proposes an improved Double DQN (DDQN) to solve the problem by reference to A* and Rapidly-Exploring Random Tree (RRT). In order to achieve the rich experiments in experience replay, the initialization of robot in each training round is redefined based on RRT strategy. In addition, reward for the free positions is specially designed to accelerate the learning process according to the definition of position cost in A*. The simulation experimental results validate the efficiency of the improved DDQN, and robot could successfully learn the ability of obstacle avoidance and optimal path planning in which DQN or DDQN has no effect.

【4】 Developing efficient transfer learning strategies for robust scene recognition in mobile robotics using pre-trained convolutional neural networks 标题：利用预先训练的卷积神经网络开发移动机器人鲁棒场景识别的高效转移学习策略

作者：Hermann Baumgartl,Ricardo Buettner 机构：UniversityofBayreuth 备注：18 pages, 1 figures, 10 tables. Submitted to IEEE Transactions on Robotics (T-RO) 链接：https://arxiv.org/abs/2107.11187 摘要：我们提出了四种不同的鲁棒转移学习和数据增强策略，用于鲁棒移动场景识别。通过在广泛使用的Event8、Scene15、Stanford40和MIT67数据集上训练三个mobile-ready（EfficientNetB0、MobileNetV2、MobileNetV3）和两个大规模基线（VGG16、ResNet50）卷积神经网络结构，我们展示了我们的转移学习策略的泛化能力。此外，我们还利用KTH-Idol2数据库测试了我们的迁移学习策略在视点和光照变化下的鲁棒性。此外，还评估了推理优化技术在不同迁移学习策略下对系统总体性能和鲁棒性的影响。实验结果表明，在移动场景识别中，采用迁移学习、微调和扩展数据增强相结合的方法，可以提高识别的准确性和鲁棒性。我们使用各种基线卷积神经网络获得了最新的结果，并且在具有挑战性的移动机器人位置识别中显示了对光照和视点变化的鲁棒性。 摘要：We present four different robust transfer learning and data augmentation strategies for robust mobile scene recognition. By training three mobile-ready (EfficientNetB0, MobileNetV2, MobileNetV3) and two large-scale baseline (VGG16, ResNet50) convolutional neural network architectures on the widely available Event8, Scene15, Stanford40, and MIT67 datasets, we show the generalization ability of our transfer learning strategies. Furthermore, we tested the robustness of our transfer learning strategies under viewpoint and lighting changes using the KTH-Idol2 database. Also, the impact of inference optimization techniques on the general performance and the robustness under different transfer learning strategies is evaluated. Experimental results show that when employing transfer learning, Fine-Tuning in combination with extensive data augmentation improves the general accuracy and robustness in mobile scene recognition. We achieved state-of-the-art results using various baseline convolutional neural networks and showed the robustness against lighting and viewpoint changes in challenging mobile robot place recognition.

【5】 Preliminary investigation into how limb choice affects kinesthetic perception 标题：肢体选择对运动知觉影响的初步研究

作者：Mohit Singhala,Amy Chi,Maria Coleman,Jeremy D. Brown 备注：Accepted as Works-in-Progress paper to World Haptics 2019 链接：https://arxiv.org/abs/2107.11174 摘要：我们对如何从上肢实时整合触觉信息来执行复杂的双手任务的理解有限，这是人类通常用来执行不同难度任务的能力。为了理解如何利用来自两个肢体的信息来创建一个统一的感知，首先必须分别研究两个肢体。强调中枢神经系统（CNS）在解释身体内部动力学中的作用的流行理论似乎表明，两个上肢对外部刺激应该同样敏感。然而，有经验证明，我们上肢在形状辨别等任务中存在知觉差异，因此有必要研究肢体选择对动觉知觉的影响。在这篇手稿中，我们开始分别评估两个前臂刚度的显著差异（JND）。早期的研究结果证实了需要更彻底地研究肢体选择对动觉知觉的影响。 摘要：We have a limited understanding of how we integrate haptic information in real-time from our upper limbs to perform complex bimanual tasks, an ability that humans routinely employ to perform tasks of varying levels of difficulty. In order to understand how information from both limbs is used to create a unified percept, it is important to study both the limbs separately first. Prevalent theories highlighting the role of central nervous system (CNS) in accounting for internal body dynamics seem to suggest that both upper limbs should be equally sensitive to external stimuli. However, there is empirical proof demonstrating a perceptual difference in our upper limbs for tasks like shape discrimination, prompting the need to study effects of limb choice on kinesthetic perception. In this manuscript, we start evaluating Just Noticeable Difference (JND) for stiffness for both forearms separately. Early results validate the need for a more thorough investigation of limb choice on kinesthetic perception.

【6】 Investigating the effects of exploration dynamics on stiffness perception 标题：探索动力对僵硬知觉影响的研究

作者：Mohit Singhala,Jeremy D. Brown 备注：Accepted as Works-in-Progress paper at World Haptics 2019 链接：https://arxiv.org/abs/2107.11173 摘要：人在回路遥操作机器人系统（HiLTS）的效用部分取决于它能提供给操作者的反馈质量。虽然机器人与环境之间的动态相互作用通常可以被感知或建模，但人-机器人界面的动态耦合往往被忽略。然而，通过刀柄实现灵巧的操作需要仔细考虑人类的触觉感知，因为它与人类在人机界面上不断变化的肢体阻抗有关。在这篇手稿中，我们根据参与者的自然探索策略，在一个简单的单自由度旋转动觉装置上以三种不同的角速度执行刚度感知任务。我们评估了探索速度作为肢体阻抗替代测量的性能影响，结果表明需要进一步研究在主动探索下，人体如何将其身体动力学知识纳入动觉知觉。 摘要：The utility of Human-in-the-loop telerobotic systems (HiLTS) is driven in part by the quality of feedback it can provide to the operator. While the dynamic interaction between robot and environment can often be sensed or modeled, the dynamic coupling of the human-robot interface is often overlooked. Enabling dexterous manipulation through HiLTS however, will require careful consideration of human haptic perception as it relates to the human's changing limb impedance at the human-robot interface. In this manuscript, we present results from a stiffness perception task run on a simple 1-DoF rotational kinesthetic device at three different angular velocities, based on participant's natural exploration strategy. We evaluated performance effects of exploration velocity as a proxy measurement for limb impedance and the results indicate the need to further investigate how the human body incorporates its knowledge of the body dynamics in kinesthetic perception under active exploration.

【7】 Towards an understanding of how humans perceive stiffness during bimanual exploration 标题：了解人类在双手探索过程中是如何感知僵硬的

作者：Mohit Singhala,Jacob Carducci,Jeremy D. Brown 备注：Accepted as Works-in-Progress paper at Haptics Symposium 2020 链接：https://arxiv.org/abs/2107.11172 摘要：在这篇论文中，一个实验台和相关的心理物理学范式提出了理解人们如何辨别扭转僵硬使用手腕旋转他们的前臂。在试验台的特点是两个1自由度旋转动觉触觉装置。一个自适应楼梯被用来评估JNDs的刚度辨别任务，参与者通过旋转前臂探索虚拟扭转弹簧。在四种不同的勘探模式下，对7种不同条件下的JND进行了评估：双手、单手、单手位移的双手反馈和双手位移的单手反馈。判别结果将为进一步研究僵硬知觉的变化提供依据。 摘要：In this paper, an experimental testbed and associated psychophysical paradigm are presented for understanding how people discriminate torsional stiffness using wrist rotation about their forearm. Featured in the testbed are two 1-DoF rotary kinesthetic haptic devices. An adaptive staircase was used to evaluate JNDs for a stiffness discrimination task where participants explored virtual torsion springs by rotating their forearms. The JNDs were evaluated across seven different conditions, under four different exploration modes: bimanual, unimanual, bimanual feedback for unimanual displacement, and unimanual feedback for bimanual displacement. The discrimination results will inform future investigation into understanding how stiffness percepts vary.

【8】 Aggressive Visual Perching with Quadrotors on Inclined Surfaces 标题：斜面上四旋体具攻击性的视觉栖息

作者：Jeffrey Mao,Guanrui Li,Stephen Nogar,Christopher Kroninger,Giuseppe Loianno 机构： the vehiclemust generate and execute dynamically feasible trajectoriesrespecting the actuator and sensor constraints despite the 1The authors are with the New York University, Tandon School of En-gineering 备注：None 链接：https://arxiv.org/abs/2107.11171 摘要：自主微型飞行器（mav）有可能被用于监视和监测任务。通过栖息和凝视一个或多个位置，空中机器人可以节省能源，同时增加他们的总任务时间，而无需积极飞行。本文利用视觉和惯性传感技术，研究了具有四个小转子的倾斜表面上自主栖息的估计、规划和控制问题。我们的重点是规划和执行动态可行的轨迹导航和栖息到一个理想的目标位置与船上传感和计算。我们的计划者还通过利用一个有效的算法来支持某些类别的非线性全局约束，这个算法已经过数学验证。车载摄像机和IMU同时用于状态估计和推断机器人/目标的相对定位。该方案在有限的计算单元上实时运行。实验结果验证了该方法的有效性，包括在倾斜表面上悬停位置的大幅度偏移，角速率高达600度/秒，加速度高达10米/秒/秒。 摘要：Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for surveillance and monitoring tasks. By perching and staring on one or multiple locations aerial robots can save energy while concurrently increasing their overall mission time without actively flying. In this paper, we address the estimation, planning, and control problems for autonomous perching on inclined surfaces with small quadrotors using visual and inertial sensing. We focus on planning and executing of dynamically feasible trajectories to navigate and perch to a desired target location with on board sensing and computation. Our planner also supports certain classes of nonlinear global constraints by leveraging an efficient algorithm that we have mathematically verified. The on board cameras and IMU are concurrently used for state estimation and to infer the relative robot/target localization. The proposed solution runs in real-time on board a limited computational unit. Experimental results validate the proposed approach by tackling aggressive perching maneuvers with flight envelopes that include large excursions from the hover position on inclined surfaces up to 90$^\circ$, angular rates up to 600~deg/s, and accelerations up to 10m/s^2.

【9】 Technical Report: Distributed Sampling-based Planning for Non-Myopic Active Information Gathering 标题：技术报告：基于分布式抽样的非近视主动信息收集规划

作者：Mariliza Tzes,Yiannis Kantaros,George J. Pappas 备注：Accepted to IROS2021 链接：https://arxiv.org/abs/2107.11163 摘要：研究了多机器人系统的主动信息采集问题。具体而言，我们认为机器人的任务是减少在复杂环境中演化的动态隐藏状态的不确定性。现有的大多数信息收集方法都是集中式的，因此，它们不能应用于分布式机器人团队，因为这些团队无法与中心用户进行通信。为了解决这一问题，我们提出了一种新的基于分布式采样的规划算法，该算法可以显著提高机器人和目标的可伸缩性，同时降低计算成本。在我们的非近视方法中，所有机器人都建立在平行的局部树中，探索信息空间和相应的运动空间。当机器人构造各自的局部树时，通过分布式Kalman滤波器与邻居进行通信，以交换和聚集关于隐藏状态的局部信念。我们证明了该算法是概率完全和渐近最优的。我们提供了大量的仿真结果，证明了所提出的算法的可扩展性，它可以解决大规模，多机器人信息收集任务，这是计算上的挑战，集中的方法。 摘要：This paper addresses the problem of active information gathering for multi-robot systems. Specifically, we consider scenarios where robots are tasked with reducing uncertainty of dynamical hidden states evolving in complex environments. The majority of existing information gathering approaches are centralized and, therefore, they cannot be applied to distributed robot teams where communication to a central user is not available. To address this challenge, we propose a novel distributed sampling-based planning algorithm that can significantly increase robot and target scalability while decreasing computational cost. In our non-myopic approach, all robots build in parallel local trees exploring the information space and their corresponding motion space. As the robots construct their respective local trees, they communicate with their neighbors to exchange and aggregate their local beliefs about the hidden state through a distributed Kalman filter. We show that the proposed algorithm is probabilistically complete and asymptotically optimal. We provide extensive simulation results that demonstrate the scalability of the proposed algorithm and that it can address large-scale, multi-robot information gathering tasks, that are computationally challenging for centralized methods.

【10】 Bio-inspired Rhythmic Locomotion in a Six-Legged Robot 标题：六足机器人的仿生节律运动

作者：Advait Lonkar,Sarthak Khoche,Shrisha Rao 备注：6 pages, 8 figures 链接：https://arxiv.org/abs/2107.11125 摘要：开发一个六足机器人或六足机器人的运动框架是一项复杂的任务，需要大量的硬件和计算。在这篇论文中，我们提出了一个仿生框架的六足动物的运动。我们的运动模型从蟑螂的结构中得到启发，蟑螂的中枢神经系统相当简单，因此我们的模型计算成本低，控制机制也比较简单。我们认为四肢形态的六足动物，相应的中枢模式生成器为其四肢，肢体间协调需要产生适当的模式在其四肢。我们还设计了两个实验来验证我们的运动模型。我们的第一个实验模拟了蟑螂和它的捕食者之间的捕食-被捕食动力学。我们的第二个实验使用了一种基于强化学习的算法，提出了我们的运动模型的实现。这些实验表明，该模型将有助于实现实际的六足机器人设计。 摘要：Developing a framework for the locomotion of a six-legged robot or a hexapod is a complex task that has extensive hardware and computational requirements. In this paper, we present a bio-inspired framework for the locomotion of a hexapod. Our locomotion model draws inspiration from the structure of a cockroach, with its fairly simple central nervous system, and results in our model being computationally inexpensive with simpler control mechanisms. We consider the limb morphology for a hexapod, the corresponding central pattern generators for its limbs, and the inter-limb coordination required to generate appropriate patterns in its limbs. We also designed two experiments to validate our locomotion model. Our first experiment models the predator-prey dynamics between a cockroach and its predator. Our second experiment makes use of a reinforcement learning-based algorithm, putting forward a realization of our locomotion model. These experiments suggest that this model will help realize practical hexapod robot designs.

【11】 A Flexible Exoskeleton for Collision Resilience 标题：一种用于抗碰撞的柔性外骨骼

作者：Ricardo de Azambuja,Hassan Fouad,Giovanni Beltrame 机构： 1 University of Edinburgh 备注：Presented at ICRA 2021 - Aerial Robotics Workshop (this https URL). arXiv admin note: substantial text overlap with arXiv:2103.04423 链接：https://arxiv.org/abs/2107.11090 摘要：以节肢动物外骨骼为灵感，我们设计了一种简单、易于制造、具有柔性关节的半刚性结构，能够被动阻尼冲击能量。这种外骨骼将保护壳与机器人的主要结构融合在一起，从而将有效载荷能力的损失降到最低。我们的设计是简单的建立和定制使用廉价的组件和消费级3D打印机。我们的结果表明，我们可以建立一个亚250克，自主四直升机视觉导航，可以生存多次碰撞，显示出五倍的被动能量吸收增加，这也适用于自动电池更换，并有足够的计算能力运行深层神经网络模型。这种结构为高风险活动（例如在杂乱的环境中飞行或强化学习训练）提供了一个理想的平台，而不会损坏硬件或环境。 摘要：With inspiration from arthropods' exoskeletons, we designed a simple, easily manufactured, semi-rigid structure with flexible joints that can passively damp impact energy. This exoskeleton fuses the protective shell to the main robot structure, thereby minimizing its loss in payload capacity. Our design is simple to build and customize using cheap components and consumer-grade 3D printers. Our results show we can build a sub-250g, autonomous quadcopter with visual navigation that can survive multiple collisions, shows a five-fold increase in the passive energy absorption, that is also suitable for automated battery swapping, and with enough computing power to run deep neural network models. This structure makes for an ideal platform for high-risk activities (such as flying in a cluttered environment or reinforcement learning training) without damage to the hardware or the environment.

【12】 3D Radar Velocity Maps for Uncertain Dynamic Environments 标题：面向不确定动态环境的三维雷达测速图

作者：Ransalu Senanayake,Kyle Beltran Hatch,Jason Zheng,Mykel J. Kochenderfer 备注：Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 链接：https://arxiv.org/abs/2107.11039 摘要：未来的城市交通概念包括地面和空中车辆的混合，在拥挤的环境中具有不同程度的自主性。在这样的动态环境中，单凭占用地图不足以进行安全路径规划。安全高效的交通需要对三维交通流进行推理，并对不确定性进行适当建模。可以采用几种不同的方法来绘制三维速度图。本文探讨了一种贝叶斯方法，捕捉我们在地图给定的训练数据的不确定性。该方法将空间坐标投影到高维特征空间，然后应用贝叶斯线性回归进行预测，并量化估计中的不确定性。在一组空中和地面数据集上，我们证明了这种方法是有效的，比其他几种方法更具可扩展性。 摘要：Future urban transportation concepts include a mixture of ground and air vehicles with varying degrees of autonomy in a congested environment. In such dynamic environments, occupancy maps alone are not sufficient for safe path planning. Safe and efficient transportation requires reasoning about the 3D flow of traffic and properly modeling uncertainty. Several different approaches can be taken for developing 3D velocity maps. This paper explores a Bayesian approach that captures our uncertainty in the map given training data. The approach involves projecting spatial coordinates into a high-dimensional feature space and then applying Bayesian linear regression to make predictions and quantify uncertainty in our estimates. On a collection of air and ground datasets, we demonstrate that this approach is effective and more scalable than several alternative approaches.

【13】 Resource Efficient Mountainous Skyline Extraction using Shallow Learning 标题：基于浅层学习的资源高效山地天际线提取

作者：Touqeer Ahmad,Ebrahim Emami,Martin Čadík,George Bebis 机构：∗Vision and Security Technology Lab, University of Colorado at Colorado Springs, USA, †Department of Computer Science and Engineering, University of Nevada, Reno, USA, Brno University of Technology, Czech Republic 备注：Accepted at International Joint Conference on Neural Networks, 2021 链接：https://arxiv.org/abs/2107.10997 摘要：天际线在山地视觉地理定位、行星探测器/无人机定位/导航以及虚拟/增强现实应用中起着关键作用。本文提出了一种新的山区天际线检测方法，采用浅层学习方法学习一组滤波器来区分天山边界和其他来自不同区域的边缘。与以前的方法不同，我们的方法要么依赖于显式特征描述子的提取及其分类，要么依赖于精细调整一般场景解析深度网络进行天空分割，我们的方法学习基于局部结构分析的线性滤波器。在测试时，对于每一个候选边缘像素，根据像素的结构张量从学习的滤波器集中选择一个滤波器，然后应用于其周围的面片。然后利用动态规划求解得到的多级图的最短路径问题，得到天山边界。所提出的方法在提供可比性能的同时，计算速度比以前的方法快，并且更适合于资源受限的平台，例如移动设备、行星漫游者和无人机。我们比较了我们提出的方法与早期的天际线检测方法使用四种不同的数据集。我们的代码可从\url获得{https://github.com/TouqeerAhmad/skyline_detection}. 摘要：Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented reality applications. We present a novel mountainous skyline detection approach where we adapt a shallow learning approach to learn a set of filters to discriminate between edges belonging to sky-mountain boundary and others coming from different regions. Unlike earlier approaches, which either rely on extraction of explicit feature descriptors and their classification, or fine-tuning general scene parsing deep networks for sky segmentation, our approach learns linear filters based on local structure analysis. At test time, for every candidate edge pixel, a single filter is chosen from the set of learned filters based on pixel's structure tensor, and then applied to the patch around it. We then employ dynamic programming to solve the shortest path problem for the resultant multistage graph to get the sky-mountain boundary. The proposed approach is computationally faster than earlier methods while providing comparable performance and is more suitable for resource constrained platforms e.g., mobile devices, planetary rovers and UAVs. We compare our proposed approach against earlier skyline detection methods using four different data sets. Our code is available at \url{https://github.com/TouqeerAhmad/skyline_detection}.

【14】 Design of the Propulsion System of Nano satellite: StudSat2 标题：纳米卫星StudSat2推进系统的设计

作者：Roshan Sah,Prabin Sherpaili,Apurva Anand,Sandesh Hegde 机构：[,] IIT Kharagpur, [,], [,] NMIT, [,] Concordia University 备注：6 pages, 13 figures, Accepted and Presented in Proceeding of International Conference on Mechanical and Aerospace Engineering (ICMAE-17), Kathmandu, Nepal on 30th Dec 2017, ASAR International Conference 链接：https://arxiv.org/abs/2107.10992 摘要：卫星应用的增加使卫星数量猛增，特别是在近地轨道。今天的主要问题是，在寿命结束后，这些卫星会成为碎片，对空间环境产生不利影响。根据欧洲航天局的国际准则，必须在卫星寿命结束后25年内使其脱离轨道。StudSat1于2010年7月12日成功发射，是印度南部七所不同工程学院的本科生在印度研制的第一颗皮卫星。现在，研究小组正在开发StudSat2，这是印度第一个双卫星任务，有两颗总质量小于10公斤的纳米卫星。本文的目的是设计一种推进系统，即冷气体推进器，以使StudSat2从原来的600公里轨道脱轨到较低的400公里轨道。推进系统主要由储罐、管道、缩扩喷管和电子执行器组成。文中还介绍了在catiav5中设计的冷气体推力器的部件，并在ANSYS中进行了结构和流动分析。利用Hohmann转移的概念对卫星进行脱轨，并用STK进行了仿真。 摘要：The increase in the application of the satellite has skyrocketed the number of satellites, especially in the low earth orbit. The major concern today is after the end of life, these satellites become debris which negatively affects the space environment. As per the international guidelines of the European Space Agency, it is mandatory to deorbit the satellite within 25 years of the end of life. StudSat1, which was successfully launched on 12th July 2010, is the first Pico satellite developed in India by undergraduate students from seven different engineering colleges across South India. Now, the team is developing StudSat2, which is India's first twin satellite mission having two nanosatellites whose overall mass is less than 10kg. This paper is aimed to design the propulsion system, cold gas thruster, to deorbit StudSat2 from its original orbit i.e. 600 km to lower orbit i.e. 400km. The propulsion system mainly consists of a storage tank, pipes, Convergent Divergent nozzle, and electronic actuators. The paper also gives information about the components of cold gas thruster, which have been designed in the CATIA V5, and the structural and flow analysis of the same has been done in ANSYS. The concept of Hohmann transfer has been used to deorbit the satellite and STK has been used to simulate it.

【15】 Automatic Construction of Lane-level HD Maps for Urban Scenes 标题：城市场景车道级高清地图的自动构建

作者：Yiyang Zhou,Yuichi Takeda,Masayoshi Tomizuka,Wei Zhan 备注：9 pages, 7 figures, 2 tables, accepted by IROS2021 链接：https://arxiv.org/abs/2107.10972 摘要：高清地图在实现完全自主方面发挥了重要作用，特别是在复杂的城市场景中。作为高清地图的关键层，车道级地图特别有用：它们包含车道和交叉口的几何和拓扑信息。然而，高清地图的大比例尺构建受到繁琐的人工标注和高昂的维护成本的限制，特别是对于道路结构复杂、标线不规则的城市场景。提出了一种基于语义粒子滤波的城市场景车道级自动映射方法。首先从联机地图数据库OpenStreetMap中将地图骨架构造为有向循环图。该方法对ego车辆的二维前视图像进行语义分割，并在真实地形投影的鸟瞰域上研究车道语义。利用OpenStreetMap，利用上述车道语义进一步推断出交叉口的车道拓扑和参考轨迹。该算法已在城市密集区进行了测试，结果表明，该算法能够准确、稳健地重建车道级高清地图。 摘要：High definition (HD) maps have demonstrated their essential roles in enabling full autonomy, especially in complex urban scenarios. As a crucial layer of the HD map, lane-level maps are particularly useful: they contain geometrical and topological information for both lanes and intersections. However, large scale construction of HD maps is limited by tedious human labeling and high maintenance costs, especially for urban scenarios with complicated road structures and irregular markings. This paper proposes an approach based on semantic-particle filter to tackle the automatic lane-level mapping problem in urban scenes. The map skeleton is firstly structured as a directed cyclic graph from online mapping database OpenStreetMap. Our proposed method then performs semantic segmentation on 2D front-view images from ego vehicles and explores the lane semantics on a birds-eye-view domain with true topographical projection. Exploiting OpenStreetMap, we further infer lane topology and reference trajectory at intersections with the aforementioned lane semantics. The proposed algorithm has been tested in densely urbanized areas, and the results demonstrate accurate and robust reconstruction of the lane-level HD map.

【16】 Learning Quadruped Locomotion Policies with Reward Machines 标题：用奖励机学习四足行走策略

作者：David DeFazio,Shiqi Zhang 机构：Binghamton University 链接：https://arxiv.org/abs/2107.10969 摘要：腿部机器人已经被证明在非结构化环境中是有效的。虽然四足机器人的运动策略学习已经取得了很大的成功，但是如何结合人类的知识来促进这一学习过程的研究却很少。在本文中，我们证明了人类知识的形式LTL公式可以应用于四足动物的运动学习奖励机（RM）的框架。仿真实验结果表明，基于RM的方法可以方便地定义不同的运动风格，并有效地学习所定义风格的运动策略。 摘要：Legged robots have been shown to be effective in navigating unstructured environments. Although there has been much success in learning locomotion policies for quadruped robots, there is little research on how to incorporate human knowledge to facilitate this learning process. In this paper, we demonstrate that human knowledge in the form of LTL formulas can be applied to quadruped locomotion learning within a Reward Machine (RM) framework. Experimental results in simulation show that our RM-based approach enables easily defining diverse locomotion styles, and efficiently learning locomotion policies of the defined styles.

【17】 Reciprocal Multi-Robot Collision Avoidance with Asymmetric State Uncertainty 标题：具有非对称状态不确定性的多机器人交互避碰

作者：Kunal Shah,Guillermo Angeris,Mac Schwager 备注：arXiv admin note: text overlap with arXiv:1905.12875 链接：https://arxiv.org/abs/2107.10956 摘要：我们给出了一大类避碰方法的一般分散公式，并证明了所有这种形式的避碰方法都是无碰撞的。这个类包括文献中作为特例的几个现有算法。然后，我们给出了这种避免碰撞方法的一个特例，CARP（通过倒数投影避免碰撞），它即使在其他代理的位置和速度的估计有噪声的情况下也是有效的。该方法的主要计算步骤是求解一个小的凸优化问题，在实际应用中，甚至在嵌入式平台上都可以快速求解，因此在计算受限的机器人（如四旋翼）上也很实用。该方法可推广到求解四转子等高动态系统的光滑多项式轨迹。我们在仿真和一组物理四转子上演示了该算法的性能。该方法对随机生成的100个障碍物的285个实例在17.12ms的中位时间内找到最优投影，并在60hz以上的四旋翼机上生成安全的多项式轨迹。本文附带了一个开源的Julia实现和ROS包。 摘要：We present a general decentralized formulation for a large class of collision avoidance methods and show that all collision avoidance methods of this form are guaranteed to be collision free. This class includes several existing algorithms in the literature as special cases. We then present a particular instance of this collision avoidance method, CARP (Collision Avoidance by Reciprocal Projections), that is effective even when the estimates of other agents' positions and velocities are noisy. The method's main computational step involves the solution of a small convex optimization problem, which can be quickly solved in practice, even on embedded platforms, making it practical to use on computationally-constrained robots such as quadrotors. This method can be extended to find smooth polynomial trajectories for higher dynamic systems such at quadrotors. We demonstrate this algorithm's performance in simulations and on a team of physical quadrotors. Our method finds optimal projections in a median time of 17.12ms for 285 instances of 100 randomly generated obstacles, and produces safe polynomial trajectories at over 60hz on-board quadrotors. Our paper is accompanied by an open source Julia implementation and ROS package.

【18】 Chance-Constrained Motion Planning using Modeled Distance-to-Collision Functions 标题：基于建模碰撞距离函数的机会约束运动规划

作者：Jacob J. Johnson,Michael C. Yip 机构： Yip are with the Department of Electrical andComputer Engineering, University of California San Diego {jjj0 2 5 备注：Paper published in CASE21 链接：https://arxiv.org/abs/2107.10953 摘要：介绍了机会约束高斯过程运动规划（CCGP-MP）算法，该算法适用于运动和状态估计不确定的机器人系统。本文的核心思想是利用高斯过程（GP）模型捕捉由于状态估计技术中的不确定性而引起的碰撞距离的变化。我们将规划问题描述为一个机会约束问题，并提出一个确定性约束，该约束使用建模的距离函数来验证机会约束。我们采用单纯形同调全局优化（SHGO）方法来寻找确定性约束函数沿轨迹的全局最小值，并用最小值来验证机会约束。在这个公式下，我们可以证明优化函数在一定条件下是光滑的，并且SHGO收敛到全局最小值。因此，CCGP-MP将始终保证计划轨迹上的所有点满足给定的机会约束。实验表明，在运动和状态不确定的情况下，CCGP-MP能生成减少碰撞、满足最优性准则的路径。我们的机器人模型和路径规划算法的实现可以在GitHub上找到。 摘要：This paper introduces Chance Constrained Gaussian Process-Motion Planning (CCGP-MP), a motion planning algorithm for robotic systems under motion and state estimate uncertainties. The paper's key idea is to capture the variations in the distance-to-collision measurements caused by the uncertainty in state estimation techniques using a Gaussian Process (GP) model. We formulate the planning problem as a chance constraint problem and propose a deterministic constraint that uses the modeled distance function to verify the chance-constraints. We apply Simplicial Homology Global Optimization (SHGO) approach to find the global minimum of the deterministic constraint function along the trajectory and use the minimum value to verify the chance-constraints. Under this formulation, we can show that the optimization function is smooth under certain conditions and that SHGO converges to the global minimum. Therefore, CCGP-MP will always guarantee that all points on a planned trajectory satisfy the given chance-constraints. The experiments in this paper show that CCGP-MP can generate paths that reduce collisions and meet optimality criteria under motion and state uncertainties. The implementation of our robot models and path planning algorithm can be found on GitHub.

【19】 PCMPC: Perception-Constrained Model Predictive Control for Quadrotors with Suspended Loads using a Single Camera and IMU 标题：PCMPC：基于单摄像机和IMU的四旋翼悬挂载荷感知约束模型预测控制

作者：Guanrui Li,Alex Tunchez,Giuseppe Loianno 机构：The authors are with the New York University, Tandon Schoolof Engineering 备注：This paper has been published at the 2021 IEEE International Conference on Robotics and Automation. Please cite this paper with the standard IEEE Conference format. We will provide the detail of the DOI information later once the Proceedings has come out 链接：https://arxiv.org/abs/2107.10888 摘要：本文研究了基于单摄像机和惯性测量单元（IMU）的四旋翼悬索有效载荷感知约束模型预测控制（PCMPC）和状态估计问题。我们设计了一种直接在系统流形空间SE（3）xS^2上描述的悬索有效载荷的后退-水平控制策略，该方法考虑了系统动力学、执行器限制和摄像机视场约束，以保证有效载荷在运动过程中的可见性。将单目摄像头、IMU和车辆的电机速度结合起来，以提供对车辆在3D空间中的状态、有效载荷状态、电缆方向和速度的估计。所提出的控制和状态估计方案在500hz的频率下在一个装有有限计算单元的小型四转子上实时运行。针对不同速度下悬索有效载荷轨迹跟踪问题，通过实验验证了该方法的有效性。 摘要：In this paper, we address the Perception--Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding--horizon control strategy for cable suspended payloads directly formulated on the system manifold configuration space SE(3)xS^2. The approach considers the system dynamics, actuator limits and the camera's Field Of View (FOV) constraint to guarantee the payload's visibility during motion. The monocular camera, IMU, and vehicle's motor speeds are combined to provide estimation of the vehicle's states in 3D space, the payload's states, the cable's direction and velocity. The proposed control and state estimation solution runs in real-time at 500 Hz on a small quadrotor equipped with a limited computational unit. The approach is validated through experimental results considering a cable suspended payload trajectory tracking problem at different speeds.