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Motion Planning for Aerial Pick-and-Place With Geometric Feasibility Constraints
This paper studies the motion planning problem of the pick-and-place of an aerial manipulator that consists of a quadcopter flying base and a Delta arm. We propose a novel partially decoupled motion planning framework to solve this problem. Compared to the state-of-the-art approaches, the proposed one has two novel features. First, it does not suffer from increased computation in high-dimensional ...Show More
Evaluation of Pedestrian Safety in a High-Fidelity Simulation Environment Framework
Lin Ma;Longrui Chen;Yan Zhang;Mengdi Chu;Wenjie Jiang;Jiahao Shen;Chuxuan Li;Yifeng Shi;Nairui Luo;Jirui Yuan;Guyue Zhou;Jiangtao Gong
2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2024 | Conference Paper |
Pedestrians' safety is a crucial factor in assessing autonomous driving scenarios. However, pedestrian safety evaluation is rarely considered by existing autonomous driving simulation platforms. This paper proposes a pedestrian safety evaluation method for autonomous driving, in which not only the collision events but also the conflict events together with the characteristics of pedestrians are fu...Show More
Angular Super-resolution Imaging of Airborne Radar by Detect-reconstruct Approach
Lu Jiao;Jiahao Shen;Yin Zhang;Yulin Huang;Deming Guo;Huaigen Zhang
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2024 | Conference Paper |
Angular resolution of airborne radar is usually poor because of its limited aperture size. The adjacent formation targets are difficult to be distinguished. To distinguish the adjacent targets by airborne radar, in this paper, a detect-reconstruct approach is proposed. First, the L1 norm is adopted to sparsely restrict the aerial targets. Second, because the targets are sparsely dispersed in the r...Show More
Influence of Radar System Parameters on The Super-resolution Performance for Airborne Forward-looking Scanning Radar
Jiahao Shen;Deqing Mao;Yin Zhang;Yulin Huang;Jianyu Yang;Yumeng Liu
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
Year: 2024 | Conference Paper |
Forward-looking scanning radar uses a servo antenna to scan the forward area and detect targets. However, due to the limitation of antenna aperture, it is difficult to obtain high-resolution images. Direct inverse convolution, a method to enhance image resolution, is ineffective due to the measurement matrix’s pathology. Various super-resolution methods of convolutional inversion have been propose...Show More
Autonomous Target Tracking and Obstacle Avoidance of A Quadrotor UAV Based on Meta-RL Algorithm
2024 43rd Chinese Control Conference (CCC)
Year: 2024 | Conference Paper |
This paper investigates the autonomous target tracking and obstacle avoidance problem of quadrotor unmanned aerial vehicles (UAVs). Based on meta reinforcement learning (Meta-RL) theory and probabilistic embeddings for actor-critic RL (PEARL), we propose a PEARL-2Buf alogrithm that improves data utilization efficiency. By introducing a meta-task set, the PEARL-2Buf model adeptly tracks diverse tar...Show More
Two-Dimensional Absolute Velocity Estimation of Moving Targets by Real-Aperture Scanning Radar Using Multiorder Range Migration Fitting Method
Two-dimensional absolute velocity estimation of moving target is a key challenge for real-aperture scanning radar because 2-D velocity estimation methods suffer from low precision or heavy computation load. For example, the traditional Hough-transform-based method can only estimate the along-track velocity with one-order range migration. In this letter, a 2-D absolute velocity estimation method is...Show More
A Fast Frequency Domain Approach Based on Gaussian Prior for Forward-Looking Scanning Radar Imaging
Shuifeng Yang;Jiahao Shen;Deqing Mao;Yin Zhang;Yulin Huang;Jianyu Yang;Jiaxin Yang
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Real aperture radar (RAR) has a limited aperture of the antenna resulting in a low azimuthal resolution. To improve the azimuthal resolution, the L2 regularization method is applied to the forward-looking scanning radar imaging. However, the traditional L2 regularization method requires an inverse operation, which results in extremely low imaging efficiency. In this paper, we propose a fast freque...Show More
Oriented Target Detection in Remote Sensing Images Based on Multi-Scale Feature Fusion and Feature Compensation
Jiahao Shen;Yangyang Li;Ruijiao Liu;Xuanwei Guo;Ronghua Shang;Licheng Jiao
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
Cited by: Papers (1)
The oriented target detection algorithm based on deep learning has made significant progress and has been widely applied in various fields, including remote sensing. However, existing methods still face challenges in large-sized targets and targets with similar backgrounds, leading to unsatisfactory detection performance in these scenarios. To address these issues, this paper proposes two modules ...Show More
A Super-Resolution Imaging Method for Forward-Looking Scanning Radar Based on Improved Total Variation
Jiahao Shen;Deqing Mao;Yin Zhang;Yulin Huang;Jianyu Yang;Zheng Wang;Haojie Peng
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Year: 2024 | Conference Paper |
In forward-looking scanning radar super-resolution imaging, the total variation (TV) regularization term is used to maintain image contour information. However, the images often suffer from false boundaries and low resolution after total variation imaging. To address this, a new method has been proposed in which the total variation adjacent unit constraint is improved to a variable multi-unit cons...Show More
Super-resolution Imaging Method for Forward-looking Scanning Radar Based on Two-layer Bayesian Model
Jiahao Shen;Deqing Mao;Yin Zhang;Yulin Huang;Haiguang Yang;Jianyu Yang
Forward-Iooking scanning radar imaging is achieved by inversion of the matrix. However, the antenna measurement matrix pathology amplifies the noise of the inversion process, making direct inverse convolution imaging a pathological issue. Therefore, it is necessary to convert this problem into a benign one. A Bayesian model consisting of two layers is utilized to model the forward-looking super-re...Show More
Anti-Jamming Strategy Design Based on Deep Q-Network for Slope-Varying LFM Signal
Shubo Chen;Weibo Huo;Cui Zhang;Jifang Pei;Yin Zhang;Yulin Huang;Jiahao Shen
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Radar systems with anti-jamming capability have become extremely important in the complex electromagnetic environment. In this paper, an anti-jamming strategy generation method based on deep Q-network (DQN) is proposed for slope-varying linear frequency modulation (SV-LFM) signals. First, the radar-jammer confrontation scenario is modeled as a Markov decision process. Subsequently, a reward functi...Show More
Visual detection of micro aerial vehicles (MAVs) is an important problem in many tasks such as vision-based swarming of MAVs. This article studies vision-based 6-D pose estimation to detect a 3-D bounding box of a target MAV, and then, estimate its 3-D position and 3-D attitude. The 3-D attitude information is critical to better estimate the target's velocity since the attitude and motion are dyna...Show More
Sensorless Brushless DC Motor Commutation Method Based on Angular Acceleration
2023 3rd International Conference on Energy, Power and Electrical Engineering (EPEE)
Year: 2023 | Conference Paper |
In variable-speed conditions, brushless direct current (BLDC) motors undergo changes in rotor speed, which affect the waveform of the motor's back electromotive force (EMF). In such scenarios, the conventional method of detecting commutation points for sensorless BLDC motors, which involves delaying the electrical angle by 30 degrees after the zero-crossing of the back EMF, cannot accurately deter...Show More
An Accurate and Efficient Two-step Velocity Estimation Method for Moving Targets for Airborne Forward-Looking Scanning Radar
Jiahao Shen;Deqing Mao;Yin Zhang;Wenjing Wang;Yulin Huang;Jianyu Yang
2023 IEEE Radar Conference (RadarConf23)
Year: 2023 | Conference Paper |
Relative velocity estimation is a key challenge for moving target detection in current forward-looking scanning radar-aerial collision avoidance systems. Since the conventional methods suffer from low precision or heavy computation load for fast-moving target motion estimation, this paper proposes an accurate and efficient two-step estimation method that improves the efficiency and accuracy. To im...Show More
Super-Resolution Method of Forward Scanning Radar Based on Weibull Distribution
Jiahao Shen;Yongwei Zhang;Xingyu Tuo;Haiguang Yang;Yulin Huang;Jianyu Yang
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Year: 2022 | Conference Paper |
Cited by: Papers (1)
To address scanning radar forward-looking sea imaging, this paper proposed a super-resolution method based on Weibull distribution. The proposed method in our work introduced the generalized Gaussian distribution and Weibull distribution to represent the prior distribution of the target and the sea clutter respectively, which are more suitable for actual sea imaging. And the corresponding objectiv...Show More
Scanning Radar Forward-Looking Superresolution Imaging Based on the Weibull Distribution for a Sea-Surface Target
Yin Zhang;Jiahao Shen;Xingyu Tuo;Haiguang Yang;Yongchao Zhang;Yulin Huang;Jianyu Yang
To realize high azimuth resolution for sea-surface targets, this article proposes a superresolution imaging method that relies on the Weibull distribution. The proposed method introduces the generalized Gaussian distribution and Weibull distribution to represent the statistical distribution function of the target prior information and sea clutter, respectively. The corresponding objective function...Show More
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