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Cooperative Localization and Tracking in Distributed Robot-Sensor Networks

Tsinghua Science and Technology 2005年第1期10卷 91-101页

作者：张帆 Guilherme S.Pereira Vijay Kumar General Robotics Automation Sensing and Perception Laboratory University of Pennsylvania Philadelphia PA USA

This paper addresses the problem of real-time position and orientation estimation of networked mobile robots in two-dimensional Euclidean space with simultaneous tracking of a rigid unknown object based on exteroceptive sensory information extracted from distributed vision systems. The sufficient and necessary conditions for team localization are proposed. A localization and object tracking approach based on statistical operators and graph searching algorithms is presented for a team of robots localized with het- erogeneous sensors. The approach was implemented in an experimental platform consisting of car-like mobile robots equipped with omnidirectional video cameras and IEEE 802.11b wireless networking. The experimental results validate the approach.

关键词： cooperative localization multi-robot formation distributed sensor network sensor data fusion

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Visual inertial odometry swarm: An autonomous swarm of vision-based quadrotors

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IEEE robotics and Automation Letters 2018年第3期3卷 1801-1807页

作者： Weinstein, Aaron Cho, Adam Loianno, Giuseppe Kumar, Vijay General Robotics Automation Sensing and Perception Laboratory University of Pennsylvania PhiladelphiaPA19104 United States

In this letter, we present the system infrastructure for a swarm of quadrotors, which perform all estimation on board using monocular visual inertial odometry. This is a novel system since it does not require an external motion capture system or GPS and is able to execute formation tasks without inter-robot collisions. The swarm can be deployed in nearly any indoor or outdoor scenario and is scalable to higher numbers of robots. We discuss the system architecture, estimation, planning, and control for the multirobot system. The robustness and scalability of the approach is validated in both indoor and outdoor environments with up to 12 quadrotors. © 2016 IEEE.

关键词： Antennas

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USING TACTILE INFORMATION IN TELErobotics

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 1992年第5期22卷 1205-1210页

作者： BROWSE, RA MCDONALD, ML Robotics and Perception Laboratory Department of Computing and Information Science Queen's University Kingston ONT Canada

An array force sensor mounted on the gripper of a robot can provide information about the contact taking place with the environment. Limited success has been attained in the use of such sensors in identifying and localizing objects. Another promising use is in the provision of tactile information for telerobotic operation. Experiments have been carried out that test a variety of tactile display methods examining human performance in judgements about robotic manipulation. The pattern of performance across the different display methods suggests that the use of the tactile data is dependent on the availability of an intersensory model of the environment.

关键词： information Telerobots Environments Judgment Robot display method HUMAN PERFORMANCE

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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Autonomous system for exploration and navigation in drift networks

Autonomous system for exploration and navigation in drift ne...

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2004 IEEE Intelligent Vehicles Symposium

作者： Bakambu, J. Nsasi Polotski, V. Cohen, P. Perception and Robotics Laboratory Ecole Polytechnique Montreal Canada

This paper describes an autonomous system for exploration and navigation within networks of tunnels, as those typically found in underground mines and caves. In the exploration mode, a remotely located supervisor instructs the system to move through successive sections of the network, gathering range data that is, then, concatenated into 2D/3D survey maps of the environment. In the navigation mode, the supervisor specifies high-level missions on the previously acquired survey maps. A motion planner, then, translates each mission into a set of consecutive navigation actions, separated by natural landmarks. Mission execution consists of detecting landmarks, self-localizing and performing the planned navigation actions.

关键词： Autonomous agents

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Inferring 2D object structure from the deformation of apparent contours

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COMPUTER VISION AND IMAGE UNDERSTANDING 1997年第2期65卷 129-147页

作者： Kakadiaris, I Metaxas, D Bajcsy, R General Robotics and Active Sensory Perception (GRASP) Laboratory Department of Computer and Information Science University of Pennsylvania Philadelphia Pennsylvania 19104

We present a new integrated approach to the two-dimensional part segmentation, shape, and motion estimation of moving multipart objects. Our technique exploits the relationship between the geometry and the observed deformations of the apparent contour of a moving multipart object and its structure. The novelty of the technique is that no prior model of the object or of its parts is employed. We develop a Part Segmentation Algorithm (PSA) that recursively recovers all the moving parts of an object by monitoring and reasoning over the changes of its deforming apparent contour. To parameterize and segment over time a deforming apparent contour, we fit initially a single deformable model whose global and local deformations over time allow us to hypothesize an underlying part structure. This hypothesis is verified by further monitoring the relative motion among the model's parts and the satisfaction of certain criteria. Upon verifying the part hypothesis, the initial deformable model is split into two or more models that better fit the apparent contour. This recursive operation allows the refinement over time of the number and shape of the extracted parts. When multiple deformable models are used to model the apparent contour of a multipart object, there is an uncertainty concerning the deformable model to which the data points should apply forces to. To address this problem, we present a new algorithm for force assignment that assigns forces from the data to multiple models. This algorithm allows partial overlap between the parts' models and the determination of their joint location. Finally, the effectiveness of the approach is demonstrated through a series of experiments involving a variety of objects. (C) 1997 Academic Press.

关键词： Computer vision

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(POSTER) Drone Detection and Localization Using Low-Cost Microphone Arrays and Convolutional Neural Networks 19

(POSTER) Drone Detection and Localization Using Low-Cost Mic...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Racinskis, Peteris Arents, Janis Greitans, Modris Institute of Electronics and Computer Science Robotics and Machine Perception Laboratory Latvia

ISBN: (纸本)9798350346497

This paper examines the possibility of using low-cost commercial off-the-shelf audio recording equipment in combination with machine learning techniques to discover the presence of hostile UAVs. A convolutional neural network (CNN) was trained to detect and localize two types of quadrotor drones using ground truth position data collected with motion capture equipment. System performance was evaluated on pre-recorded validation data sets and in realtime operation. In both cases, drones can be successfully detected and localized within the constrained working volumes studied, achieving angular accuracies in the 8-13° range. However, further work remains to be done before system feasibility in outdoor conditions can be established. © 2023 IEEE.

关键词： Drones

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When Shannon Meets Nonstochastic Information: Communication and Estimation

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IEEE Transactions on Automatic Control 2025年

作者： Zhang, Wentao Zuo, Zhiqiang Zhao, Rui Wang, Yijing Hu, Guoqiang Zhang, Hui Wang, Yaonan Hunan University School of Robotics Changsha410082 China Nanyang Technological University Continental-NTU Corporate Lab Singapore639798 Singapore Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Nanyang Technological University School of Electrical and Electronic Engineering Singapore639798 Singapore National Engineering Research Center for Robot Visual Perception and Control Changsha410082 China Hunan University College of Electrical and Information Engineering Changsha410082 China

This notes focuses on the issue of whether or not the state of a plant can be estimated when the inputs of communication channel involve noise and disturbance simultaneously. It turns out to calculate the maximum capacity of stationary memoryless multiple quasi-access channel under nonstochastic information theory. It is shown that the maximum information rate over such a channel is determined by a convex hull spanned by the zero-error capacities which are specified on the underlying sample spaces. Moreover, the state of a plant could be estimated provided that the maximal information rate is strictly greater than the topology entropy. © 1963-2012 IEEE.

关键词： Communication channels (information theory)

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Prior Distribution and perception Radius Are Important: Learning 3-D Object Detector for Autonomous Driving

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Ziming Tao Jianxu Mao Weixing Peng Yaonan Wang Junfei Yi Hui Zhang National Engineering Laboratory of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan University Changsha Hunan China National Engineering Research Center of Robot Visual Perception and Control Technology College of Robotics Hunan University Changsha Hunan China

This article proposes an efficient 3-D object detection algorithm for LiDAR point clouds in the field of autonomous driving. Currently, despite significant performance improvements in 3-D LiDAR object detection methods, there are still problems that have impact on 3-D detection accuracy. Typically, since the sampling process and grouping process introduced background points, the final regression step in the detection task would be greatly affected. To address this problem, a method named PR-SSD is proposed to retain more important foreground points during the training pipeline, improving detection accuracy. Specifically, the proposed approach utilizes prior information to guide semantic sampling, referred to as prior distributed semantic sampling (PDSS). This mechanism encourages the network to prioritize foreground targets in regression. In addition, a module named radius-aware attention multiscale grouping (RAMSG) is designed to dynamically reassign grouping weights for multiscale features. In other words, the network has adaptive detection capabilities for targets of different scales. Furthermore, PR-SSD is a single-stage detector which can be trained end-to-end. Finally, extensive experiments and evaluations on large-scale benchmarks KITTI demonstrate that our proposed method significantly enhanced 3-D object detector. In KITTI testing set, PR-SSD achieves 89.69%, 45.08%, and 80.01% detection performance for cars, pedestrians, and cyclists.

关键词： Three-dimensional displays Detectors Point cloud compression Feature extraction Semantics Object detection Laser radar Autonomous vehicles Proposals Automobiles

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A triangle feature based map-to-map matching and loop closure for 2D graph SLAM

A triangle feature based map-to-map matching and loop closur...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Jiang, Binqian Zhu, Yilong Liu, Ming Hong Kong University of Science and Technology Robotics and Multi-Perception Laboratory in Robotics Institute Hong Kong

ISBN: (纸本)9781728163215

The loop closure problem in 2D LiDAR simultaneous localization and mapping (SLAM) is interesting yet to be solved efficiently, as it suffers from a lack of information in 2D laser rangefinder readings. For this reason, we compare two grid submaps, where features and constraints are enriched, to find loops. We propose a geometric environment descriptor called a Triangle Feature (TF). It exploits the Euclidean distance constraint any three feature points in a submap can form. A 2D graph SLAM system using TF to close loops is also developed. The global maps we build outperform some popular open-source SLAM solutions, and the system can run up to 2.4 times of real-time in our experiments. © 2019 IEEE.

关键词： robotics

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