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arXiv 2025年

作者： Zhang, Qianyi Luo, Wentao Liu, Boyi Zhang, Ziyang Wang, Yaoyuan Liu, Jingtai Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin China Advanced Computing and Storage Lab Huawei 2012 Lab China Department of Electronic and Computer Engineering The Kong Kong University of Science and Technology Hong Kong

Motion planning in navigation systems is highly susceptible to upstream perceptual errors, particularly in human detection and tracking. To mitigate this issue, the concept of guidance points—a novel directional cue within a reinforcement learning-based framework—is introduced. A structured method for identifying guidance points is developed, consisting of obstacle boundary extraction, potential guidance point detection, and redundancy elimination. To integrate guidance points into the navigation pipeline, a perception-to-planning mapping strategy is proposed, unifying guidance points with other perceptual inputs and enabling the RL agent to effectively leverage the complementary relationships among raw laser data, human detection and tracking, and guidance points. Qualitative and quantitative simulations demonstrate that the proposed approach achieves the highest success rate and near-optimal travel times, greatly improving both safety and efficiency. Furthermore, real-world experiments in dynamic corridors and lobbies validate the robot’s ability to confidently navigate around obstacles and robustly avoid pedestrians. © 2025, CC BY.

关键词： Travel time

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Design and Implementation of an On-Board system for a Spider Robot 1st

Design and Implementation of an On-Board System for a Spider...

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1st International Conference on Computing and Emerging Technologies, ICCET 2023

作者： Nauman, Nasir Mustafa, Hirra Ashraf, Abrar Khalil, Hisham Department of Computer Science Superior University Lahore Pakistan Department of Computer Science Sharif College of Engineering and Technology Lahore Lahore Pakistan Embedded System and Robotics Lab Department of Technology The University of Lahore Lahore Pakistan

ISBN: (纸本)9783031776199

This paper presents the design of a system onboard spider robot for rescue services. The spider has the six-leg walking pattern that contains the total number of 18 servo motors. In order to reduce the payload, the abdomen of the spider is made with RF4 printed circuit board (PCB). Whereas, the abdomen is also used as the main structure of the robot to attach the rest of the system. Wherein, two pulse-width modulations (PWM) module are controlled by Arduino Nano, the Bluetooth module is used for communication link and bulk converter for the power supply. The spider robot is operated with an in-house developed Android application. It has been observed that the spider robot has a stable walking response along with the multiple excise performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Machine design

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Image encryption using simple algorithm on FPGA

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Telkomnika (Telecommunication Computing Electronics and Control) 2015年第4期13卷 1153-1161页

作者： Prasetio, Barlian Henryranu Setiawan, Eko Muttaqin, Adharul Computer System and Robotics Lab Faculty of Computer Science University of Brawijaya Jl. Veteran Malang Indonesia Computer System and Robotics Lab Faculty of Engineering University of Brawijaya Jl. Veteran Malang Indonesia

Data security becomes one of the things that need to be considered. The Sum of Product (SOP) Encryption is one of simple algorithm. The SOP encryption is not a public-key system to encrypt data. it is almost unbreakable through brute force method and vulnerable to attack because the encryption models have a fixed pattern. However, this drawback can be avoided through the compression process to remove the pattern file. SOP encryption algorithm can use a Boolean algebra combination functions such as AND gate and OR gate. Simple algorithm in hardware language VHSIC Hardware Description Language (VHDL) is on data bits level. The purpose of this research is implementation of image encryption algorithm to produce a quick image encryption system. From result test, the image processing time without encryption average 4.999ns/px and 13.51ns/px with encryption. © 2015 Universitas Ahmad Dahlan. All rights reserved.

关键词： Cryptography

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Study of voice data communication using network streams on dataflow programming 2

Study of voice data communication using network streams on d...

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2nd International Conference on Engineering and Technology for Sustainable Development, ICET4SD 2017

作者： Prasetio, Barlian Henryranu Syauqy, Dahnial Maulana, Rizal Setyawan, Gembong Edhi System and Robotics Lab Faculty of Computer Science University of Brawijaya Indonesia

In this paper, we implement a voice data communications between sender and receiver through Wi-Fi. The system was designed and implemented using network stream protocol which was developed by National Instruments on lab-VIEW between two devices. The device which acts as the sender was My-RIO board and the receiver device was Personal computer. The voice data communication system was tested by observing the effect of various buffer sizes on the throughput, latency and CPU usage. The result showed that the larger the buffer size being used, the throughput values were also getting bigger. However, particular buffer size made the throughput became saturated. The change on the buffer size also directly affects CPU usage. It seemed that the buffer size did not affect latency significantly. It showed that the latency was stable with an average of 13 milliseconds on voice data transmission. © The Authors, published by EDP Sciences, 2018.

关键词： Convolutional codes

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Role playing learning for socially concomitant mobile robot navigation

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CAAI Transactions on Intelligence Technology 2018年第1期3卷 49-58页

作者： Mingming Li Rui Jiang Shuzhi Sam Ge Tong Heng Lee Department of Electrical and Computer Engineering and the Social Robotics Lab Smart System Institute (SSI) National University of Singapore Singapore 117576 Singapore

In this study, the authors present the role playing learning scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks （NNs） are constructed to parameterise a stochastic policy that directly maps sensory data collected by the robot to its velocity outputs, while respecting a set of social norms. An efficient simulative learning environment is built with maps and pedestrians trajectories collected from a number of real-world crowd data sets. In each learning iteration, a robot equipped with the NN policy is created virtually in the learning environment to play itself as a companied pedestrian and navigate towards a goal in a socially concomitant manner. Thus, this process is called role playing learning, which is formulated under a reinforcement learning framework. The NN policy is optimised end-to-end using trust region policy optimisation, with consideration of the imperfectness of robot＇s sensor measurements. Simulative and experimental results are provided to demonstrate the efficacy and superiority of the proposed method.

关键词：学习环境人工智能发展现状智能技术

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Motion-oriented attention for a social gaze robot behavior 6

Motion-oriented attention for a social gaze robot behavior

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6th International Conference on Social robotics, ICSR 2014

作者： Sorostinean, Mihaela Ferland, François Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab Computer Science and System Engineering Department ENSTA-ParisTech Palaiseau France

ISBN: (纸本)9783319119724

Various studies have shown that human visual attention is generally attracted by motion in the field of view. In order to embody this kind of social behavior in a robot, its gaze should focus on key points in its environment, such as objects or humans moving. In this paper, we have developed a social natural attention system and we explore the perception of people while interacting with a robot in three different situations: one where the robot has a totally random gaze behavior, one where its gaze is fixed on the person in the interaction, and one where its gaze behavior adapts to the motion-based environmental context. We conducted an online survey and an on-site experiment with the Meka robot so as to evaluate people’s perception towards these three types of gaze. Our results show that motion-oriented gaze can help to make the robot more engaging and more natural to people. © Springer International Publishing Switzerland 2014.

关键词： Robots

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One-time password implementation on lego Mindstorms NXT

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Telkomnika (Telecommunication Computing Electronics and Control) 2014年第3期12卷 689-694页

作者： Prasetio, Barlian Henryranu Nurwarsito, Heru Kurniawan, Wijaya Computer System and Robotics Lab Program of Information Technology and Computer Science University of Brawijaya Jl. Veteran Malang Indonesia Computer Networking Lab Program of Information Technology and Computer Science University of Brawijaya Jl. Veteran Malang Indonesia

One of the factors that affect the security of a network or system is user authentication, so that at times it can be said to be no longer safe. Brute force attacks on password systems are a dominant (static) potential way to penetrate network security or user authentication systems. One way to overcome these drawbacks is to use the One Time Password (OTP) algorithm. OTP is a password security system using dynamic passwords. The password will be valid for one session only. In this research, the author will analyse the reliability of the OTP algorithm by applying it to a LEGO Mindstorms robot. The robot will be designed as part of a system where the user will be safe to enter the default password, and then the system will change the password every session. The results of the questionnaire showed that 79% of users felt more secure, but more than 60% said it was difficult to do.

关键词： Authentication

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Earth image classification design using unmanned Aerial vehicle

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Telkomnika (Telecommunication Computing Electronics and Control) 2015年第3期13卷 1021-1028页

作者： Prasetio, Barlian Henryranu Supianto, Ahmad Afif Setiawan, Gembong Edhi Setiawan, Budi Darma Cholissodin, Imam Akbar, Sabriansyah R. Computer System and Robotics Lab Program of Information Technology and Computer Science University of Brawijaya Malang65145 Indonesia Intelligent Computing and Multimedia Lab Program of Information Technology and Computer Science University of Brawijaya Malang65145 Indonesia Computer Networking Lab Program of Information Technology and Computer Science University of Brawijaya Malang65145 Indonesia

The research aims to build software that can perform the classification of earth image from UAV (Unmanned Aerial Vehicle) monitoring. The Image converted into YUV format then classified using Fuzzy Support Vector Machine (FSVM). UAVs will be used for monitoring as follows: (1) the control station, which used to send or receive data, and display the data in graphical form, (2) payload, camera captured images and send to the control station, (3) communication system using TCP/IP protocol, and (4) UAV, using X650 quad copter products. The image of the monitoring carried out on the UAV sized 256 x 256 pixels with 450 training data. It is 16x16 pixel image data. Tests performed to classify the image into 3 classes, namely agricultural area, residential area, and water area. The highest accuracy value of 77.69% obtained by the number of training data as much as 375. © 2015 Universitas Ahmad Dahlan.

关键词： Image classification

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Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car

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computers, Materials & Continua 2022年第5期71卷 2285-2302页

作者： Hajira Saleem Faisal Riaz Asadullah Shaikh Khairan Rajab Adel Rajab Muhammad Akram Mana Saleh Al Reshan Control Automotive and Robotics Lab Affiliated lab of National Center of Robotics and Automation(NCRA HEC Pakistan)and with the Department of Computer Science and Information TechnologyMirpur University of Science and Technology(MUST)Mirpur Azad Kashmir10250Pakistan College of Computer Science and Information System Najran UniversityNajran61441Saudi Arabia College of Computer Science and Engineering University of South FloridaTampa33620United States

Deep learning techniques,particularly convolutional neural networks(CNNs),have exhibited remarkable performance in solving visionrelated problems,especially in unpredictable,dynamic,and challenging *** autonomous vehicles,imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of *** this regard,globally,researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best *** has proven the superiority of metaheuristic algorithms over the manual-tuning of ***,to the best of our knowledge,these techniques are yet to be applied to address the problem of imitationlearning-based steering angle ***,in this study,we examine the application of the bat algorithm and particle swarm optimization algorithm for the optimization of the CNN model and its hyperparameters,which are employed to solve the steering angle prediction *** validate the performance of each hyperparameters’set and architectural parameters’set,we utilized the Udacity steering angle dataset and obtained the best results at the following hyperparameter set:optimizer,Adagrad;learning rate,0.0052;and nonlinear activation function,exponential linear *** per our findings,we determined that the deep learning models show better results but require more training epochs and time as compared to shallower *** show the superiority of our approach in optimizing CNNs through metaheuristic algorithms as compared with the manual-tuning *** testing was also performed using the model trained with the optimal architecture,which we developed using our approach.

关键词： Bat algorithm convolutional neural network hyperparameters metaheuristic optimization algorithm steering angle prediction

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DWT-DCT based individuals identification using robust gait feature images

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第4期8卷 113-124页

作者： Ibrahim Khalilullah, K.M. Hossain, Delowar Hamid, Ekramul Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Intelligent Robotics Lab Department of Electrical and Electronics System Engineering University of Toyama Japan Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh

Individual identification at a distance using gait features has newly gained growing interest from biometrics researchers. Most of the researchers have been shown that different covariate factors can affect different parts of the human body. In this paper, we propose a new approach that minimizes these difficulties, especially for carrying objects by combining static, dynamic, and part-based features. The Gait Features of the walking sequences are extracted by selecting only four sub bands of the Discrete Wavelet Transform (DWT) of the individual images. Moreover, Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) are implemented to extract lowest and middle frequency components that are used to create robust gait feature images (RGFIs). Then we select effective parts of the body from the Robust Gait Feature Images. After that, these parts of the body are trained using Principal Component Analysis (PCA) and Multiple Discriminant Analysis (MDA) to identify individuals. Experimental result shows promising performance in comparison with other methods. © 2015 SERSC.

关键词： Discrete cosine transforms

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