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Deep Neural Network Based Object Detection Algorithm With optimized Detection Head for Small Targets 20

Deep Neural Network Based Object Detection Algorithm With op...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Zhu, Yongchang Dong, Enzeng Tong, Jigang Yang, Sen Zhang, Zufeng Li, Wenyu Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory 391 Binshui West Road Tianjin China Nankai University College of Artificial Intelligence 94 Weijin Road Tianjin China

ISBN: (纸本)9798350320831

Target detection is a significant research direction in the realm of computer vision, aimed at analyzing and localizing targets in input images to obtain their categories and locations. However, this task is faced with several challenges in complex scenarios, such as large variations in target scales, similarity to the background, dense number, and overlapping with each other, making it difficult for the target detection model to extract different scales and discriminative target features adaptively, leading to low detection accuracy and weak generalization ability. To tackle the aforementioned problems, this study proposes a novel approach by optimizing the detection head of the model, invoking decoupled detection heads, dividing the classification and localization tasks, and optimizing for small targets. this approach effectively reduces the false detection rate and the missed detection rate, enabling the network to better discriminate and recognize distant objects as well as objects of relatively small size. Moreover, the proposed approach outperforms the yolov7 model by 0.8% in the COCO dataset, not only improving the accuracy of detecting distant and small targets but also exhibiting better performance in conventional target detection. Additionally, this approach is capable of handling small targets, overlapping targets, or relatively dense targets, significantly expanding its practical use range. © 2023 IEEE.

关键词： Object detection

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Stiffness-based Offline Toolpath Error Compensation for Robotized Incremental Forming

Stiffness-based Offline Toolpath Error Compensation for Robo...

引用

automation, control and Robots (ICACR), international conference on

作者： Walid K. Shaker Alexandr Klimchik Institute of Robotics and Computer Vision Innopolis University Innopolis Russia Lincoln Centre for Autonomous Systems Research (L-CAS) School of Computer Science University of Lincoln Lincoln United Kingdom

this paper addresses the challenge of the poor accuracy and the toolpath deviation in Incremental Sheet Forming (ISF) caused by the forming forces applied to the workpiece. the paper proposes an offline toolpath error compensation approach based on stiffness analysis. A truncated cone was used as a test case and the numerical simulation of the ISF process was conducted on Abaqus CAE software to extract forming forces corresponding to toolpath points. the compensation algorithm is based on the Virtual Joint Method (VJM) and is implemented on a FANUC R-2000iC/165F robot using RoboDK API for MATLAB. the results show that the deviation of the robot tool due to the forming forces may reach up to 20 mm which can be handled by the compensated toolpath. Finally, the study proposes an overall process for the stiffness-based correction algorithm.

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Bioinspired Segmented Hybrid Bending Pneumatic Actuators for Rehabilitation/Assisting Training

Bioinspired Segmented Hybrid Bending Pneumatic Actuators for...

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international conference on Mechatronics and Machine vision in Practice (M2VIP)

作者： Kai Li Daohui Zhang Yaqi Chu Xingang Zhao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

Soft pneumatic actuators/robotics have received dramatic attention in rehabilitation/assisting scenarios, owing to their intrinsic elasticity and simple control strategies for producing desired motions. However, most existing soft pneumatic bending actuators show homogenous/continuous deformation and the profile mismatch between the SPBAs and interacted objects, which hinder compatible motion and precise operations. this paper presents the design, modeling, and testing of pneumatic bioinspired segmented hybrid bending actuators (SHBAs) for rehabilitation interactions. the segmented structure inspired by the anatomy of the human finger, i.e., the soft-joint/rigid-bone configuration, makes the proposed actuator match the finger better than those of the traditional continuous structure. To efficiently predict the bending angles and the motion trajectories of the bioinspired actuator, a static model was developed relating the geometrical parameters. In addition, we build a finite-element model to quantitatively verify the experimental results and theoretical analysis simultaneously. Furthermore, underactuated finger rehabilitation gloves with SHBAs demonstrated their potential in assisting ADLs scenarios.

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Adaptive tracking control of unknown state target for CPSs subjected to cyberattacks

Adaptive tracking control of unknown state target for CPSs s...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Yizhou Sun Ya Zhang School of Cyber Science and Engineering Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Automation Southeast University Nanjing China

ISBN: (纸本)9781665476881

In this study, an adaptive controller for Cyber-Physical Systems(CPSs) subjected to cyberattacks is proposed to track a class of target system with unknown inputs and states. Firstly, an estimation strategy is proposed to adaptively estimate the unknown inputs and states of target on the basis of finite impulse response (FIR) filter. Secondly, due to the existence of cyberattacks in CPSs, an adaptive tracking control scheme with designed compensation signal is constructed to stabilize the system performance which might be damaged by attacks, where Lyapunov function related to adaptive estimated factor is adopted to prove that the CPSs are able to track the target under attacks. In the last part, a numerical experiment is implemented to demonstrate the validity of the theoretical results.

关键词： Target tracking Adaptive systems Finite impulse response filters System performance Estimation Lead control systems

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Robot control with multitasking of brain-computer interface

Robot control with multitasking of brain-computer interface

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international conference on control, automation, robotics and vision (ICARCV)

作者： Yajun Zhou Zilin Lu Yuanqing Li School of Automation Science and Engineering South China University of Technology Guangzhou China Research Center for Brain-Computer Interface Pazhou Lab Guangzhou China

ISBN: (纸本)9781665476881

Brain-computer interfaces (BCI) have been extensively researched to assist people with motor paralysis in controlling external devices such as a robotic limb. However, most BCI systems required participants to focus on a single task, limiting their ability to generate other mental or physical activities. therefore, people's performance of the BCI-based robotic control in multitasking was discussed, as eight healthy subjects performed motor-related tasks of motor imagery and two-handed balancing ball movement, while simultaneously performing visuospatial attention to asynchronously trigger “drinking” actions of a humanoid robot arm with accuracies of 90% and 87.5%, respectively. the online results indicate that the BCI-based robot control system developed for multi-task conditions has a high potential for human augmentation.

关键词： Performance evaluation Robot control Neuroprostheses Multitasking Manipulators Human augmentation Brain-computer interfaces

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Move2Hear: Active Audio-Visual Source Separation 18

Move2Hear: Active Audio-Visual Source Separation

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18th IEEE/CVF international conference on Computer vision (ICCV)

作者： Majumder, Sagnik Al-Halah, Ziad Grauman, Kristen Univ Texas Austin Austin TX 78712 USA Facebook AI Res Mountain View CA USA

ISBN: (纸本)9781665428125

We introduce the active audio-visual source separation problem, where an agent must move intelligently in order to better isolate the sounds coming from an object of interest in its environment. the agent hears multiple audio sources simultaneously (e.g., a person speaking down the hall in a noisy household) and it must use its eyes and ears to automatically separate out the sounds originating from a target object within a limited time budget. Towards this goal, we introduce a reinforcement learning approach that trains movement policies controlling the agent's camera and microphone placement over time, guided by the improvement in predicted audio separation quality. We demonstrate our approach in scenarios motivated by both augmented reality (system is already co-located with the target object) and mobile robotics (agent begins arbitrarily far from the target object). Using state-of-the-art realistic audio-visual simulations in 3D environments, we demonstrate our model's ability to find minimal movement sequences with maximal payoff for audio source separation. Project: http://***/projects/move2hear.

关键词： Budget control

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Challenges in Virtual Testing of Autonomous Vehicles

Challenges in Virtual Testing of Autonomous Vehicles

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international conference on control, automation, robotics and vision (ICARCV)

作者： Andrea Piazzoni Roshan Vijay Jim Cherian Lyu Chen Justin Dauwels ERI@N Interdisciplinary Graduate Programme Nanyang Technological University Singapore Centre of Excellence for Testing & Research of AVs Nanyang Technological University Singapore School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Dept. of Microelectronics Fac. EEMCS TU Delft Delft

ISBN: (纸本)9781665476881

the worldwide development of Autonomous Vehicles (AVs) has also encouraged the use of software simulators for virtual testing of AVs. However, the effectiveness of the AV simulators is constrained by numerous challenges, such as their computational cost and lack of fidelity in specific areas. In this paper, we describe the modality of virtual testing and its benefits for AV development and validation. Moreover, we summarize and provide an overview of the state-of-the-art AV simulators, their limitations, and the current directions toward improvement.

关键词： automation Software Safety Computational efficiency Autonomous vehicles Standards Robots

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TFMarker: A Tangible Fiducial Pattern for Enabling Camera-assisted Guided Landing in SubT Environments

TFMarker: A Tangible Fiducial Pattern for Enabling Camera-as...

引用

international conference on control, automation and Systems ( ICCAS)

作者： Mario A. V. Saucedo Akash Patel Niklas Dahlquist Yifan Bai Björn Lindqvist Christoforos Kanellakis George Nikolakopoulos Department of Computer Electrical and Space Engineering Robotics & AI Group Luleå University of Technology Luleå Sweden

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Visual servoing plays a crucial role in robotics, spanning across a great spectrum of applications from autonomous cars to aerial manipulation. this article proposes TFMarker, a novel tangible fiducial pattern for enabling camera-assisted guided landing of UAVs by using the visual features from color markers as the main source of information. TFMarker is structured around a 4-point fiducial marker, allowing for accurate, precise, and consistent pose estimation in different environments and lighting conditions, while also offering resilience to motion blur. the presented detection framework is based on a three-step architecture, where the first step uses Gaussian and color filtering in addition to morphological operation in order to generate a robust detection of the markers. the second step uses the Gift Wrapping Algorithm, to organize the same-color markers based on their relative positioning with respect to the off-color marker. Finally, the Perspective-n-Point optimization problem is solved in order to extract the pose (i.e. position and orientation) of the proposed pattern with respect to the vision sensor. the efficacy of the proposed scheme has been extensively validated in indoor and SubT environments for the task of autonomous landing using a custom-made UAV. the experimental results showcase the performance of the proposed method, which presents a better detection rate in both environments while retaining similar accuracy and precision to the baseline approach. For the video of the experimental evaluation please refer to the following link: https://***/Zh13OObp15Q

关键词： Visualization Accuracy Filtering Color vision sensors Autonomous aerial vehicles Visual servoing Wrapping Optimization Morphological operations

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Informed Guided Rapidly-exploring Random Trees*-Connect for Path Planning of Walking Robots

Informed Guided Rapidly-exploring Random Trees*-Connect for ...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Dominik Belter Institute of Robotics and Machine Intelligence Poznan University of Technology Poznan Poland

ISBN: (纸本)9781665476881

In this paper, we deal with the problem of full-body path planning for walking robots. the state of walking robots is defined in multi-dimensional space. Path planning requires defining the path of the feet and the robot's body. Moreover, the planner should check multiple constraints like static stability, self-collisions, collisions with the terrain, and the legs' workspace. As a result, checking the feasibility of the potential path is time-consuming and influences the performance of a planning method. In this paper, we verify the feasibility of sampling-based planners in the path planning task of walking robots. We identify the strengths and weaknesses of the existing planners. Finally, we propose a new planning method that improves the performance of path planning of legged robots.

关键词： Legged locomotion automation Path planning Planning Quadrupedal robots Collision avoidance Task analysis

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Photogrammetry-based Dynamic Path Tracking of Industrial Robots Using Adaptive Neuro-PID control Method and Robust Kalman Filter

Photogrammetry-based Dynamic Path Tracking of Industrial Rob...

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international conference on Autonomous Robots and Agents, ICARA

作者： Jianyu Tang Tao Zhou Ehsan Zakeri Tingting Shu Wen-Fang Xie Department of Mechanical Industrial & Aerospace Engineering Concordia University Montreal Canada

this paper proposes a novel accurate dynamic path tracking (DPT) method for industrial robots based on photogrammetry sensors and an adaptive neuro-PID (ANPID) control method. First, the pose of the robot's end-effector is detected by the photogrammetry sensor (C-Track stereo camera). It passes through a robust Kalman filter to reduce the noise in the signals. then, the filtered signals are fed to the ANPID, whose gains are tuned online using an adaptive multi-layer perceptron neural network (AMLPNN). the steepest descent optimization method is adopted online. the cost function is the least mean square of the system states errors. Experimental results on FANUC M-20iA robot show the tracking accuracy reaches ±0.08mm and ±0.04deg, which exhibits the superiority of the proposed method over the conventional methods such as PID (tracking error±0.2mm and ±0.1deg) [4].

关键词： Uncertainty Service robots Heuristic algorithms Robot kinematics Robot vision systems Aerodynamics Industrial robots

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