Multirotor Unmanned Aerial Vehicles (UAV)s flight performance rely on accurate estimation of their attitude and position for stable and robust control, which is essential for precise path following and management. Tra...
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ISBN:
(数字)9798331529734
ISBN:
(纸本)9798331529741
Multirotor Unmanned Aerial Vehicles (UAV)s flight performance rely on accurate estimation of their attitude and position for stable and robust control, which is essential for precise path following and management. Traditional methods for estimating six Degrees of Freedom (DoF) parameters, such as position, orientation, and velocity, often combine data from Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and vision sensors using complex algorithms for fusion and filtering. This approach can lead to challenges in real-time processing and robustness to environmental variations. In this paper, we propose a novel approach that leverages deep learning and incorporates a physics-informed loss function based on monocular vision data to enhance the accuracy of these sensors by eliciting position and heading data from a trained model of flow detection, enhanced with a mathematical model of optical flow. We implement a fusion of camera, IMU, magnetometer, and ultrasonic sensors for robust and accurate 6 DoF data acquisition in multirotor systems. Our proposed framework utilizes Convolutional Neural Networks (CNN)s to directly learn the mapping between sensor data and 6 DoF parameters. By jointly processing visual and inertial data in an end-to-end manner, our model exploits the complementary information provided by each sensor modality, thereby enhancing estimation accuracy and robustness to external disturbances. We demonstrate the effectiveness of our approach through extensive experiments on real-world multirotor platforms, show-casing significant improvements in pose and motion estimation accuracy compared to conventional methods. Our fusion deep learning framework offers a promising pathway for enhancing the autonomy and performance of multi rotor UAVs.
To address the challenges associated with shape sensing of continuum manipulators (CMs) using Fiber Bragg Grating (FBG) optical fibers, we feature a unique shape sensing assembly utilizing solely a single Optical Freq...
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Problem of adaptive state observer synthesis for linear time-varying (LTV) system with unknown time-varying parameter and delayed output measurements is considered. State observation problem has attracted the attentio...
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As robotic navigation techniques in perception and planning advance, mobile robots increasingly venture into off-road environments involving complex traversability. However, selecting suitable planning methods remains...
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We present closed-form expressions for marginalizing and conditioning Gaussians onto linear manifolds, and demonstrate how to apply these expressions to smooth nonlinear manifolds through linearization. Although margi...
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Deformable objects especially large-size de-formable objects grasping is unappreciated but widespread in industrial applications (e.g., clothes recycling). While it encounters several challenges, for example, the exis...
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ISBN:
(数字)9798350375022
ISBN:
(纸本)9798350375039
Deformable objects especially large-size de-formable objects grasping is unappreciated but widespread in industrial applications (e.g., clothes recycling). While it encounters several challenges, for example, the existing methods didn’t take large-size deformable objects into account, no typical boundary of deformable objects. To solve the challenges, we proposed a grasp detection framework consisting of a self-trained object detection network, an instance segmentation module, and a grasp pose generation pipeline. The experiments were successfully conducted on the industrial laundry mock-up with an 88.9% success ratio. The experiments result indicates the effectiveness of the proposed framework on spatial-constrained large-size deformable objects grasping in clutter.
This paper proposes the ProxFly, a residual deep Reinforcement Learning (RL)-based controller for close proximity quadcopter flight. Specifically, we design a residual module on top of a cascaded controller (denoted a...
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Currently, permanent vascular stents are fabricated using titanium and stainless steel implants that are nondegradable and offer high stability, but they have certain disadvantages. For example, the prolonged expositi...
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We present an autonomous aerial system for safe and efficient through-the-canopy fruit counting. Aerial robot applications in large-scale orchards face significant challenges due to the complexity of fine-tuning fligh...
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Vibratory treatment is widely used in various industries for performing finishing technological operations, e.g., lapping, polishing, glazing, strengthening (hardening), etc. The problems of maximizing the treatment a...
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