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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Optimized Design of Frequency-Reconfigurable Microstrip Patch Antenna with RF MEMS Shunt Switches for Enhanced Return Loss Performance at 3.4 GHz

Optimized Design of Frequency-Reconfigurable Microstrip Patc...

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2024 International Conference on Smart Systems for Applications in Electrical Sciences, ICSSES 2024

作者： Murali Narayanan, R. Ramkumar, G. Anitha, G. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Automation and Robotics Engineering Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of ECE Chennai India

ISBN: (纸本)9798350364040

This work offers an optimized design of a reconfigurable microstrip patch antenna coupled with RF MEMS shunt capacitor switches to improve performance at 3.4 GHz. The antenna, with dimensions of 40 × 45 × 1.6 mm, was constructed and simulated using the HFSS (High-Frequency Structural Simulator). By utilizing RF MEMS technology to achieve frequency agility in HFSS, the antenna allows for dynamic reconfiguration of its operating frequency. Comparing the simulation results to prior designs, a significant improvement in return loss of -40 dB and gain of 4.1dBi, as well as enhanced impedance matching and frequency coverage, is observed. These results underscore the potential of the proposed approach for multiband applications in contemporary wireless communication systems. Future optimization and application-specific modifications of the optimized antenna design are highly promising. Subsequent investigations may focus on optimizing design parameters to achieve superior performance measures such as reduced size, radiation efficiency, and bandwidth. Additionally, the antenna's reconfigurable feature enables its use in various applications, including cognitive radio, satellite communications, and Internet of Things (IoT) devices. Exploring these possibilities could drive the evolution of wireless communication technology to meet the changing requirements of diverse applications. © 2024 IEEE.

关键词： Cognitive radio

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Enhanced RF Characteristics of Frequency Reconfigurable Microstrip Patch Antenna using Aperture-Coupled Feeding at 5 GHz 4

Enhanced RF Characteristics of Frequency Reconfigurable Micr...

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Murali Narayanan, R. Ramkumar, G. Anitha, G. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Automation and Robotics Engineering Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Ece Chennai India

ISBN: (纸本)9798350354218

This work presents a novel antenna design that makes use of the aperture coupled feeding technique. By carefully arranging them in different layers, the antenna patch and feed line maximize performance through efficient energy coupling. The antenna is 40 x 22 x 1.01 mm3 overall. The patch, measuring 17.85 x 16 mm2, is placed on atop the second substrate, and the feed line is positioned underneath the first substrate. To improve the antenna's RF properties and optimize its size, a thorough parametric study was carried out. Important factors, such as the height of the second patch and the breadth and length of the patch and substrates, were the focus of this iterative optimization process. The ultimate design therefore demonstrated its efficacy in directed radiation with a gain value of 5.4 dBi. The antenna is appropriate for point-to-point communication, Wi-Fi systems, radar systems, medical imaging equipment, and industrial automation systems. It runs at a frequency of 5 GHz. The design has the potential for high-performance applications in various sectors because of its enhanced RF performance and adaptability. © 2024 IEEE.

关键词： Slot antennas

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Evaluating Feature Importance in the Context of Simulation-Based Inference for Cortical Circuit Parameter Estimation 17th

Evaluating Feature Importance in the Context of Simulatio...

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17th International Conference on Brain Informatics, BI 2024

作者： Sandron, Alessandro Valero, Alejandro Orozco García, Juan Miguel Mancini, Gabriele Pelayo, Francisco Morillas, Christian Panzeri, Stefano Martínez-Cañada, Pablo University of Padua Padua Italy University of Granada Granada Spain Istituto Italiano di Tecnologia Genoa Italy Department of Pharmacy and Biotechnology University of Bologna Bologna Italy Hamburg Germany Department of Computer Engineering Automation and Robotics University of Granada Granada Spain

ISBN: (纸本)9789819632930

Extracellular electrophysiology recordings capturing the activity of neuronal populations, e.g., Local Field Potentials (LFPs), have offered important insights into cortical dynamics. Yet there is still a lack of clarity about how features and characteristics of these extracellular potentials relate to the properties and function of the underlying neural populations. Mechanistic models combined with simulation-based inference (SBI) algorithms have emerged as an effective strategy for developing predictive tools that fit well with available empirical data and can be used to predict key parameters that describe neural activity. Numerous SBI techniques rely on summary statistics or interpretable features to approximate the likelihood or posterior. However, at present, a significant challenge is assessing how each feature impacts the SBI model’s predictions. Here, we developed an approach to determine feature importance in the context of cortical circuit parameter inference. We first created a dataset that includes a million distinct simulations from a spiking cortical microcircuit model of recurrently connected excitatory and inhibitory populations. Biophysics-based causal filters were coupled with spikes to generate realistic LFP data. We then extracted a set of meaningful features from simulated LFP data that were used to train an SBI algorithm. To evaluate feature importance, we employed SHAP values, a prominent tool in machine learning for interpreting the contribution of each feature to the prediction outcomes. Our findings demonstrate the effectiveness of our approach in pinpointing the most critical features, such as dfa, rs_range, low_freq_power or transition_variance, for inferring parameters of a recurrent cortical circuit model based on electrophysiological data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electrophysiology

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Towards Disturbance Rejection in Feature Pyramid Network

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 946-958页

作者： Hu, Xiaobo Xu, Wei Gan, Yi Su, Jianbo Zhang, Jun Shanghai Jiao Tong University Joint Institute of UM-SJTU Shanghai200240 China Shanghai Jiao Tong University Research Center of Intelligent Robotics Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

The multiscale problem is one of the challenging topics in the object detection field. Among the current studies toward this problem, feature pyramid network (FPN) has been shown a superior performance. The core principle of FPN is a mapping for the detectable objects into hierarchy features. These features are designed with different size of receptive fields, which brings good scale invariance in the classification and localization subtasks. However, a disturbance of information dilution is generated by the assignment for the detectable objects into different features. This dilution disturbance is associated with the convolution or pooling operation during the hierarchy feature extraction process. Both of the imprecise localization information in the top features and the fuzzy classification information in the bottom ones limit the performance of FPN. Aiming at the disturbance rejection problem of information dilution, this article presents a feature compensation method. A cross compensation between the semantic information and the localization information in hierarchy features is used to enhance the vanilla FPN. Then, the evaluation metrics in an object detection task are examined. Not only the overall performance, but also the respective metrics for multiscale objects validate a considerable improvement of the FPN with a disturbance compensation mechanism. The experimental results demonstrate an effectiveness of the proposed method in this article. © 2020 IEEE.

关键词： Object detection

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Human Robot Interaction: Identifying Resembling Emotions Using Dynamic Body Gestures of Robot 3

Human Robot Interaction: Identifying Resembling Emotions Usi...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Ali, Sara Mehmood, Faisal Iqbal, Khawaja Fahad Ayaz, Yasar Sajid, Muhammad Sial, Muhammad Baber Malik, Muhammad Faiq Javed, Kashif Department of Robotics and Artificial Intelligence Islamabad Pakistan National University of Sciences and Technology H-12 Department of Robotics and Artificial Intelligence Islamabad Pakistan National University of Sciences and Technology H-12 Islamabad Pakistan School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9798350322125

Natural social interaction between a human and robot requires perception ability of robot for complex social behaviors and in turn displaying the learnt emotional behavior during interaction. The emotions expressed with body language are one of the key parameters during Human-Robot Interaction (HRI). This research focuses on extending the concept of affective non-verbal human-robot interaction using full body gestures for closely resembling emotion in absence of intricate facial expressions. The movements of head, torso, legs, and arms are used to link body movements and gestures of a bi-pedal humanoid robot with 28 closely resembling emotions. Variation of speed, frequency, and joint angles of the robot are the key features used for expressing a specific emotion. This research uses Russell's circumplex model to define 8 primary emotional categories which are further grouped into closely associated emotions resembling each other. 33 participants were involved in experimentation to authenticate different emotions using body gestures of robot. Each participant performed 28 trials in which emotions were displayed at random to recognize the state of robot. The results showed an average accuracy of 79.69%. The study authenticates that perceived emotions are highly dependent on body movements, postures, and selected features. This design model can therefore be used for even conveying the closely resembling emotions. © 2023 IEEE.

关键词： Anthropomorphic robots

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Effect of Tine Shaped Furrow Opener on Dry Soil Using Discrete Element Modelling

Effect of Tine Shaped Furrow Opener on Dry Soil Using Discre...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Abdul Mohiz Fazal E Nasir Kamran Shah Department of Mechatronics Engineering University of Engineering & Technology Peshawar Pakistan Advanced Robotics & Automation Lab National Center of Robotics & Automation Peshawar Pakistan

Tillage of the soil is the most important consideration when it comes to the implementation of agricultural practices. Increases in crop yield has been achieved through a variety of agricultural practices thanks to the discoveries of various agricultural experts. The planting process is the one that has the greatest impact on the crop's overall health. The hull can be more precisely prepared for the seed-planting trench with the assistance of furrows. A variety of furrow openers are currently undergoing the implantation process. Studying dynamic systems that are discontinuous in nature can be done with the help of discrete element modelling. The simulation of a tine-shaped furrow opener using the EDEM package software was carried out for three different speeds. When the speed of an object increases, so does the force it exerts on it. Additionally, the length of an object has an effect on the force it exerts. Additionally, taken into consideration were the profiles that were generated in the soil. To carry out statistical validation of the results analysis of variation (ANOVA) was done. The results provided a basis for calculating a confidence level of 95%. For the furrow openers, it was suggested that a speed of 0.495 meters per second, which is equivalent to 1.76 kilometers per hour, be used.

关键词： Meters Industries automation Force Crops Soil Software

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Speed and Distance Detection for Highway Traffic using Python

Speed and Distance Detection for Highway Traffic using Pytho...

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IEEE International Conference on System, Computation, automation and Networking (ICSCAN)

作者： G Renuka Devi S. Athiyan k. Ilan Thamizh V. Hema Varthini Department of Robotics and Automation Manakula Vinayagar Institute of Technology Puducherry

This Python -based scheme presents an innovative approach to bolstering road safety by harnessing the power of computer vision and machine learning. The primary objective is to provide drivers with crucial real-time information for informed lane change decisions, thereby reducing the risk of accidents. The system integrates advanced techniques such as object detection, tracking algorithms, and depth estimation to analyze video feeds from highway cameras. The system's core functionality involves estimating the speed and distance of vehicles on the highway. Object detection algorithms, including YOLO, SSD, and Faster R-CNN, are employed to identify and track vehicles in the video feed. Depth estimation techniques enhance accuracy by determining relative distances between vehicles. Machine learning algorithms, such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs), predict future positions and speeds, enabling the system to identify potential conflicts.

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Object detection methods for Image-based Visual Servoing of 6-DOF Industrial robot

Object detection methods for Image-based Visual Servoing of ...

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2022 IEEE Region 10 Symposium, TENSYMP 2022

作者： Krishnan, Megha G Ashok, S. Adi Shankara Institute of Engineering and Technology Department of Robotics and Automation India National Institute of Technology Department of Electrical Engineering Calicut India

ISBN: (数字)9781665466585

ISBN: (纸本)9781665466585

The employment of robots in manufacturing industries is on the rise due to the need for automated industrial operations. Visual servoing is a well-advanced method of controlling the robot movement based on visual sensor feedback. In image-based visual servoing (IBVS), the image features at the final pose implicitly define the desired camera pose relative to the target. The major issue associated with image-based visual servoing of industrial manipulators is the identification and tracking of object to be manipulated from the image sequence. In this paper, two methods are employed to detect the object for providing image feature vector in the visual servoing feedback loop. One method employs a robust and fast algorithm called SpeededUp Robust Features (SURF) for image comparison. Another method utilizes the method of comparing measuring the properties of the image region and comparing with the given image to detect the object. These algorithms are applied in the image-based visual servoing system for obtaining the image feature error to drive the system. Real-time experiments are conducted in IBVS system where IRB 1200 industrial robot manipulator is active with eye-in-hand camera. The results illustrate the improved performance of the object identification algorithms. © 2022 IEEE.

关键词： Object detection

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A Sensorless Speed Control of High-Speed BLDC Motor Using Variable Slope SMO

A Sensorless Speed Control of High-Speed BLDC Motor Using Va...

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作者： Ok, Sangjae Xu, Zhenyao Lee, Dong-Hee Department of Mechatronics Engineering Kyungsung University Busan48434 Korea Republic of State Key Laboratory of Robotics Shenyang Institute of Automation The Chinese Academy of Sciences Shenyang110016 China

Low-power and high-speed BLDC(Brushless DC) motor is widely used in vacuum cleaners. This paper presents a sensorless speed control scheme for a high-speed BLDC motor of a hand-stick vacuum cleaner using a variable slope sliding mode observer(SMO). The SMO using the signum function is very effective for the sensorless estimation of the BLDC motor. However, the chattering effect on the slide surface from the signum function decreases the sensorless performance in the wide speed range. The sigmoid function instead of the signum function can reduce the chattering effect. However, the convergence is inversely proportional to the reduced chattering effect. In order to reduce the chattering effect and keep the proper convergence performance, the proposed method uses a variable acceleration slope of the sigmoid function. In the low-speed range, the acceleration slope of SMO is decreased to reduce the chattering. And, it is increased to improve the convergence in the high-speed region. The acceleration slope of the sigmoid function is designed as a function of the estimated speed to keep the constant convergence with reduced chattering in the sensorless speed and position estimation. In order to verify the proposed sensorless control scheme, 115 krpm speed 540W BLDC motor for a vacuum cleaner is tested with various SMO methods. In the experimental results, the proposed method shows better sensorless speed control performance in the wide speed range. © 2023 IEEE.

关键词： Sensorless control

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