检索结果-内蒙古大学图书馆

Real-Time Joint Simulation of LiDAR Perception and Motion Planning for Automated Driving

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Huang, Zhanhong Zhang, Xiao Huang, Xinming The Department of Electrical & Computer Engineering Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States

Real-time perception and motion planning are two crucial tasks for autonomous driving. While there are many research works focused on improving the performance of perception and motion planning individually, it is still not clear how a perception error may adversely impact the motion planning results. In this work, we propose a joint simulation framework with LiDAR-based perception and motion planning for real-time automated driving. Taking the sensor input from the CARLA simulator with additive noise, a LiDAR perception system is designed to detect and track all surrounding vehicles and to provide precise orientation and velocity information. Next, we introduce a new collision bound representation that relaxes the communication cost between the perception module and the motion planner. A novel collision checking algorithm is implemented using line intersection checking that is more efficient for long distance range in comparing to the traditional method of occupancy grid. We evaluate the joint simulation framework in CARLA for urban driving scenarios. Experiments show that our proposed automated driving system can execute at 25 Hz, which meets the real-time requirement. The LiDAR perception system has high accuracy within 20 meters when evaluated with the ground truth. The motion planning results in consistent safe distance keeping when tested in CARLA urban driving scenarios. © 2023, CC BY.

关键词： Motion planning

Stream-Based Ground Segmentation for Real-Time LiDAR Point Cloud Processing on FPGA

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Zhang, Xiao Huang, Zhanhong Antony, Garcia Gonzalez Jachimczyk, Witek Huang, Xinming Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA01609 United States The Computer Vision and Autonomous Vehicles Team The MathWorks MA01760 United States The Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA01609 United States

This paper presents a novel and fast approach for ground plane segmentation in a LiDAR point cloud, specifically optimized for processing speed and hardware efficiency on FPGA hardware platforms. Our approach leverages a channel-based segmentation method with an advanced angular data repair technique and a cross-eight-way flood-fill algorithm. This innovative approach significantly reduces the number of iterations while ensuring the high accuracy of the segmented ground plane, which makes the stream-based hardware implementation possible. To validate the proposed approach, we conducted extensive experiments on the SemanticKITTI dataset. We introduced a bird’s-eye view (BEV) evaluation metric tailored for the area representation of LiDAR segmentation tasks. Our method demonstrated superior performance in terms of BEV areas when compared to the existing approaches. Moreover, we presented an optimized hardware architecture targeted on a Zynq-7000 FPGA, compatible with LiDARs of various channel densities, i.e., 32, 64, and 128 channels. Our FPGA implementation operating at 160 MHz significantly outperforms the traditional computing platforms, which is 12 to 25 times faster than the CPU-based solutions and up to 6 times faster than the GPU-based solution, in addition to the benefit of low power consumption. Copyright © 2024, The Authors. All rights reserved.

关键词： computer graphics equipment

Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Lin, Fangzhou Liu, Haotian Zhou, Haoying Hou, Songlin Yamada, Kazunori D. Fischer, Gregory S. Li, Yanhua Zhang, Haichong K. Zhang, Ziming Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Dell Technologies HopkintonMA01748 United States Graduate School of Information Sciences Tohoku University Sendai980-8579 Japan Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States Department of Electrical & Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

3D point clouds enhanced the robot’s ability to perceive the geometrical information of the environments, making it possible for many downstream tasks such as grasp pose detection and scene understanding. The performance of these tasks, though, heavily relies on the quality of data input, as incomplete can lead to poor results and failure cases. Recent training loss functions designed for deep learning-based point cloud completion, such as Chamfer distance (CD) and its variants (e.g. HyperCD [1]), imply a good gradient weighting scheme can significantly boost performance. However, these CD-based loss functions usually require data-related parameter tuning, which can be time-consuming for data-extensive tasks. To address this issue, we aim to find a family of weighted training losses (weighted CD) that requires no parameter tuning. To this end, we propose a search scheme, Loss Distillation via Gradient Matching, to find good candidate loss functions by mimicking the learning behavior in backpropagation between HyperCD and weighted CD. Once this is done, we propose a novel bilevel optimization formula to train the backbone network based on the weighted CD loss. We observe that: (1) with proper weighted functions, the weighted CD can always achieve similar performance to HyperCD, and (2) the Landau weighted CD, namely Landau CD, can outperform HyperCD for point cloud completion and lead to new state-of-the-art results on several benchmark datasets. Our demo code is available at https://***/Zhang-VISLab/ IROS2024-LossDistillationWeightedCD. © 2024, CC0.

关键词： Deep learning

Guiding the Last Centimeter: Novel Anatomy-Aware Probe Servoing for Standardized Imaging Plane Navigation in Robotic Lung Ultrasound

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ma, Xihan Zeng, Mingjie Hill, Jeffrey C. Hoffmann, Beatrice Zhang, Ziming Zhang, Haichong K. The Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Diagnostic Medical Sonography School of Medical Imaging and Therapeutics MCPHS University WorcesterMA01608 United States The Department of Emergency Medicine Beth Israel Deaconess Medical Center BostonMA02215 United States The Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Biomedical Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Navigating the ultrasound (US) probe to the standardized imaging plane (SIP) for image acquisition is a critical but operator-dependent task in conventional freehand diagnostic US. Robotic US systems (RUSS) offer the potential to enhance imaging consistency by leveraging real-time US image feedback to optimize the probe pose, thereby reducing reliance on operator expertise. However, determining the proper approach to extracting generalizable features from the US images for probe pose adjustment remains challenging. In this work, we propose a SIP navigation framework for RUSS, exemplified in the context of robotic lung ultrasound (LUS). This framework facilitates automatic probe adjustment when in proximity to the SIP. This is achieved by explicitly extracting multiple anatomical features presented in real-time LUS images and performing non-patient-specific template matching to generate probe motion towards the SIP using image-based visual servoing (IBVS). The framework is further integrated with the active-sensing end-effector (A-SEE), a customized robot end-effector that leverages patient external body geometry to maintain optimal probe alignment with the contact surface, thus preserving US signal quality throughout the navigation. The proposed approach ensures procedural interpretability and inter-patient adaptability. Validation is conducted through anatomy-mimicking phantom and in-vivo evaluations involving five human subjects. The results show the framework's high navigating precision with the probe correctly located at the SIP for all cases, exhibiting positioning error of under 2 mm in translation and under 2 degrees in rotation. These results demonstrate the navigation process's capability to accommodate anatomical variations among patients. Copyright © 2024, The Authors. All rights reserved.

关键词： Probes

Evaluating Vulnerability of Chiplet-Based Systems to Contactless Probing Techniques

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Deric, Aleksa Mitard, Kyle Tajik, Shahin Holcomb, Daniel Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute United States

Driven by a need for ever increasing chip performance and inclusion of innovative features, a growing number of semiconductor companies are opting for all-inclusive System-on-Chip (SoC) architectures. Although Moore's Law has been able to keep up with the demand for more complex logic, manufacturing large dies still poses a challenge. Increasingly the solution adopted to minimize the impact of silicon defects on manufacturing yield has been to split a design into multiple smaller dies called chiplets which are then brought together on a silicon interposer. Advanced 2.5D and 3D packaging techniques that enable this kind of integration also promise increased power efficiency and opportunities for heterogeneous integration. However, despite their advantages, chiplets are not without issues. Apart from manufacturing challenges that come with new packaging techniques, disaggregating a design into multiple logically and physically separate dies introduces new threats, including the possibility of tampering with and probing exposed data lines. In this paper we evaluate the exposure of chiplets to probing by applying laser contactless probing techniques to a chiplet-based AMD/Xilinx VU9P FPGA. First, we identify and map interposer wire drivers and show that probing them is easier compared to probing internal nodes. Lastly, we demonstrate that delay-based sensors, which can be used to protect against physical probes, are insufficient to protect against laser probing as the delay change due to laser probing is only 0.792ps even at 100% laser power. © 2024, CC BY-NC-SA.

关键词： Programmable logic controllers

A Miniaturized Prototype for Continuous Noninvasive Transcutaneous Oxygen Monitoring

学校读者我要写书评

暂无评论

A Miniaturized Prototype for Continuous Noninvasive Transcut...

2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022

作者： Kahraman, Burak Vakhter, Vladimir Costanzo, Ian Bu, Guixue Foroozan, Foroohar Guler, Ulkuhan Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Analog Devices Inc. WilmingtonMA01887 United States

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

Luminescent oxygen sensing is employed for measuring the partial pressure of oxygen diffusing through the skin, named transcutaneous oxygen. Two well-known approaches are intensity- and lifetime-based measurements for assessing transcutaneous oxygen. The lifetime-based technique is preferable as it offers lower susceptibility to optical path changes and reflections compared to the intensity-based method. High-resolution lifetime capturing is critical to accurate transcutaneous oxygen measurements from the human body. This study proposes a miniaturized prototype based on a multimodal analog front end, ADPD4101, and custom firmware. We have demonstrated that the prototype could detect small changes in the lifetime with high resolution, showing its suitability for future human subject tests. We implemented the prototype on a 68 mm × 43 mm printed circuit board (PCB) and consumes the power ×of 39 mW. © 2022 IEEE.

关键词： Oxygen

Realistic Data Generation for 6D Pose Estimation of Surgical Instruments

学校读者我要写书评

暂无评论

Realistic Data Generation for 6D Pose Estimation of Surgical...

IEEE International Conference on Robotics and Automation (ICRA)

作者： Juan Antonio Barragan Jintan Zhang Haoying Zhou Adnan Munawar Peter Kazanzides Department of Computer Science Johns Hopkins University Baltimore MD USA Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Automation in surgical robotics has the potential to improve patient safety and surgical efficiency, but it is difficult to achieve due to the need for robust perception algorithms. In particular, 6D pose estimation of surgical instruments is critical to enable the automatic execution of surgical maneuvers based on visual feedback. In recent years, supervised deep learning algorithms have shown increasingly better performance at 6D pose estimation tasks; yet, their success depends on the availability of large amounts of annotated data. In household and industrial settings, synthetic data, generated with 3D computer graphics software, has been shown as an alternative to minimize annotation costs of 6D pose datasets. However, this strategy does not translate well to surgical domains as commercial graphics software have limited tools to generate images depicting realistic instrument-tissue interactions. To address these limitations, we propose an improved simulation environment for surgical robotics that enables the automatic generation of large and diverse datasets for 6D pose estimation of surgical instruments. Among the improvements, we developed an automated data generation pipeline and an improved surgical scene. To show the applicability of our system, we generated a dataset of 7.5k images with pose annotations of a surgical needle that was used to evaluate a state-of-the-art pose estimation network. The trained model obtained a mean translational error of 2.59mm on a challenging dataset that presented varying levels of occlusion. These results highlight our pipeline’s success in training and evaluating novel vision algorithms for surgical robotics applications.

关键词： Training Visualization Medical robotics Three-dimensional displays Annotations Instruments Pose estimation

The Impact of Motion Artifacts on Transcutaneous Oxygen Measurements

学校读者我要写书评

暂无评论

The Impact of Motion Artifacts on Transcutaneous Oxygen Meas...

2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Vakhter, Vladimir Kahraman, Burak Bu, Guixue Foroozan, Foroohar Beidleman, Beth A. Guler, Ulkuhan Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA01609 United States Analog Devices Inc. WilmingtonMA01887 United States United States Army Research Institute of Environmental Medicine NatickMA01887 United States

ISBN: (纸本)9798350300260

Transcutaneous oxygen monitoring is a noninvasive method of measuring the partial pressure of oxygen permeating through the skin (PtcO2). Its medical significance lies in correlating changes in PtcO2 with alterations in arterial oxygen levels. Luminescent lifetime-based oxygen sensing is suitable for measuring PtcO2 with miniaturized systems like wearables, where a consistent and reliable signal is crucial for accurate measurements. This study presents the preliminary results of examining the impact of motion artifacts on PtcO2 measurements based on the luminescent lifetime-based technique. To conduct these tests, a custom wearable PtcO2 monitor was used, and its onboard accelerometer was calibrated. The study included two human subjects who executed basic forearm movements (lateral and medial rotations and flexion). The pilot tests showed that the luminescent lifetime-based technique is notably resilient against motion artifacts, as the change in lifetime values during motions did not exceed 4%. Importantly, we believe this study is the first in the literature to specifically investigate the impact of motion artifacts on the lifetime-based PtcO2 measurements through human tests. © 2023 IEEE.

关键词：

STREAM: Software Tool for Routing Efficiently Advanced Macrofluidics

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Wang, Lehong Kendre, Savita V. Liu, Haotian Nemitz, Markus P. Robotic Materials Group Department of Robotics Engineering Worcester Polytechnic Institute MA01609 United States Department of Computer Science Worcester Polytechnic Institute MA01609 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA01609 United States

The current fabrication and assembly of fluidic circuits for soft robots relies heavily on manual processes;as the complexity of fluidic circuits increases, manual assembly becomes increasingly arduous, error-prone, and time-consuming. We introduce a software tool that generates printable fluidic networks automatically. We provide a library of fluidic logic elements that are easily 3D printed from thermoplastic polyurethanes using Fused Deposition Modeling only. Our software tool and component library allow the development of arbitrary soft digital circuits. We demonstrate a variable frequency ring oscillator and a full adder. The simplicity of our approach using FDM printers only, democratizes fluidic circuit implementation beyond specialized laboratories. Our software is available on GitHub (https://***/roboticmaterialsgroup/FluidLogic) Copyright © 2023, The Authors. All rights reserved.

关键词： computer software