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8th International Conference on Sustainable Information Engineering and Technology, SIET 2023

作者： Irsal, Riyandi Banovbi Putera Laksono, Blessius Sheldo Putra Utaminingrum, Fitri Computer Vision Research Group Universitas Brawijaya Indonesia Robotics and Embedded System Research Group Universitas Brawijaya East Java Indonesia

ISBN: (纸本)9798400708503

In this life, many people with disabilities lose the opportunity to live better than others. especially people with physical disabilities who may not have mobility like us. Physical disability is caused by several things, some from birth or disease and also an accident. People with physical disabilities who have difficulty walking require a wheelchair to be able to move. However, hands and arms must be used to operate the wheelchair. We found a way to solve the problem. we plan to move the wheelchair with eyeball movement as navigation. this solution does not only solve the problem of physical disability. we can also reduce contact to often hold the wheelchair. To detect eyeball movement, we use the Faster R-CNN method. This method if we compare it with other methods has competitive accuracy. From the results we have, we get a mAP value of more than 0.853 from each class. © 2023 ACM.

关键词： Wheelchairs

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Low-Cost Hand Gesture Control for Swarm Quadrotor using Wearable Device in Indoor Environments

Low-Cost Hand Gesture Control for Swarm Quadrotor using Wear...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Muhammad Luthfi Harwidjaya Aufaclav Zatu Kusuma Frisky Bilqis Hafsah Ababiel Adhiwirya Panyananda Suryadi Alfahri Rifki Fahrezi Bambang Nurcahyo Prastowo Department of Computer Science and Electronics Embedded System and Robotics Lab UGM Indonesia

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

The control device for quadrotor aerial vehicles has garnered considerable attention in development endeavors aimed at enhancing user interface and interaction in indoor environments. Quadrotor control mechanisms rely on sophisticated remote transmitters, which often come at a substantial cost and necessitate a proficient skill set for operation to adjust in limited space. Consequently, an innovative paradigm to harness wearable technology as a means of controlling multi-drone systems, thereby streamlining user engagement. This novel approach harnesses 2.4 GHz radio frequency communication and leverages hand gestures as a conduit for motion inputs, which are subsequently processed via a machine learning algorithm augmented by a 9 axis Inertial Measurement Unit (IMU) sensor suite. The primary objective of this system pertains to the effective control of multi drones in the context of obstacle avoidance missions in indoor space. As such, this system embodies considerable promise as an alternative avenue for multi-drone system control, characterized by its intuitive nature and enhanced user accessibility.

关键词： Space missions Simulation Aerospace electronics User interfaces Control systems Indoor environment Wearable devices

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Multi-Agent Reinforcement Learning for Cooperative Vehicle Motion Control

Multi-Agent Reinforcement Learning for Cooperative Vehicle M...

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International Conference on Intelligent Transportation

作者： Kenan Ahmic Johannes Ultsch Jonathan Brembeck Darius Burschka Institute of System Dynamics and Control at the German Aerospace Center (DLR) Wessling Germany Chair of Robotics Artificial Intelligence and Embedded Systems Technical University of Munich (TUM) Munich Germany

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

The longitudinal and lateral low-level motion control of multiple vehicles within a platoon is a challenging task, since several different control objectives need to be solved: (i) Each vehicle in the platoon needs to follow the reference path, (ii) the leading vehicle needs to drive with a desired reference velocity, and (iii) the following vehicles need to maintain a safe spacing distance to their respective preceding vehicle. Typically, several distinct controllers are developed for each task individually, which increases both the engineering effort as well as the susceptibility to errors. We address this issue and present a cooperative low-level vehicle motion controller based on Multi-Agent Reinforcement Learning (MARL) that is able to solve all of the above-mentioned control objectives for both the leading vehicle and the following vehicles. Therefore, we apply parameter sharing within MARL to update a single control policy in a centralized fashion using the experiences of all vehicles in the environment. Additionally, we utilize the concept of agent indication during the training process and enable the policy to specialize on the control objectives of the vehicle it is currently controlling. This leads to a unifying control approach and makes the development of further controllers redundant. The simulative assessment demonstrates the effectiveness of learned policy and shows that it is able to successfully solve all of the above-mentioned control objectives for both vehicles roles, even on unseen paths.

关键词： Training Process control Reinforcement learning Drives Vectors Robustness Collision avoidance Intelligent transportation systems

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Real-Time Slip Detection using Tactile Information 9

Real-Time Slip Detection using Tactile Information

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9th Edition of IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2021

作者： Phukan, Nabasmita Kakoty, Nayan M. Sharma, Manoj Jorhat Engineering College Department of Instrumentation Engineering Jorhat Assam India Tezpur University Embedded System and Robotics Lab Assam India

ISBN: (纸本)9781665432405

Slip detection is of paramount importance for stabilized grasping of objects by a prosthetic hand. This paper presents a real-time slip detection framework using a data glove customized with force sensors. The data glove can acquire grasping force with a root mean square error (RMSE) of ±0.21 Newton. A finite state machine (FSA) algorithm was implemented for estimating the instances of slip occurrence as features. Support Vector Machine (SVM) with polynomial and radial basis function (RBF) kernel, k-nearest neighbor (k-NN), Naive Bayes (NB) and Random Forest algorithms were evaluated for detection of slip. An average accuracy of 94% and 98% was achieved using polynomial and RBF kernel SVM respectively. Further NB, k-NN and Random Forest algorithms resulted into an average accuracy of 96 %, 99 % and 100 % respectively. These experimental results show that the proposed framework is very useful for slip detection using tactile force information. It demonstrated robustness of FSA with machine learning algorithms for real-time slip detection and thereby holds promise for stabilized grasping by a prosthetic hand. © 2021 IEEE.

关键词： Support vector machines

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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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ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce NAS Space for Heterogeneous Pipeline of CNNs 29

ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce ...

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29th IEEE International Conference on Parallel and Distributed systems, ICPADS 2023

作者： Duan, Huijuan Wang, Danghui Zhao, Xingting Mei, Kuizhi Wang, Jihe Polytechnical University School of Computer Science Northwestern Xi'an China Northwestern Polytechnical University Engineering Research Center of Embedded System Integration Ministry of Education Xi'an China Xi'An Jiaotong University Institute of Artificial Intelligence and Robotics Xi'an China Northwestern Polytechnical University Natl. Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi'an China

ISBN: (纸本)9798350330717

Efficiently deploying neural network models on heterogeneous edge systems faces unique challenges. Two major issues are underutilized pipelines caused by hardware heterogeneity and explosive growth of architecture search space. To address these challenges, we propose ExpoNAS, a framework enabling fast deployment-oriented neural architecture search on heterogeneous platforms. ExpoNAS evaluates model partitioning and deployability before search to meet accuracy and latency constraints. However, repeated partitioning leads to exponential growth in architecture search space. We first observe a strong correlation between operational exposure and accuracy improvement, and then we propose an exposure-based reduction technique that excludes the operations of low exposure. By removing these non-critical operations, the exposure-based pruning successfully reduces architecture search time. Our experiments on popular datasets show that the ExpoNAS pipelined design improves execution efficiency by a factor of 2 compared to traditional batch processing. Without compromising accuracy, ExpoNAS is able to reduce the architecture search time by 47.5% for discovering high-accuracy networks, compared to the SOTA NAS strategies. © 2023 IEEE.

关键词： heterogeneous systems NAS pipeline mapping search space reduction

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Grasp planning for flexible production with small lot sizes based on CAD models using GPIS and Bayesian optimization

arXiv

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arXiv 2021年

作者： Lin, Jianjie Rickert, Markus Knoll, Alois Robotics and Embedded System Department of Informatics Technische Universität München Munich Germany

Grasp planning for multi-fingered hands is still a challenging task due to the high nonlinear quality metrics, the high dimensionality of hand posture configuration, and complex object shapes. Analytical-based grasp planning algorithms formulate the grasping problem as a constraint optimization problem using advanced convex optimization solvers. However, these are not guaranteed to find a globally optimal solution. Data-driven based algorithms utilize machine learning algorithm frameworks to learn the grasp policy using enormous training data sets. This paper presents a new approach for grasp generation by formulating a global optimization problem with Bayesian optimization. Furthermore, we parameterize the object shape utilizing the Gaussian Process Implicit Surface (GPIS) to integrate the object shape information into the optimization process. Moreover, a chart defined on the object surface is used to refine palm pose locally. We introduced a dual optimization stage to optimize the palm pose and contact points separately. We further extend the Bayesian optimization by utilizing the alternating direction method of multipliers (ADMM) to eliminate contact optimization constraints. We conduct the experiments in the graspit! Simulator that demonstrates the effectiveness of this approach quantitatively and qualitatively. Our approach achieves a 95% success rate on various commonly objects with diverse shapes, scales, and weights. © 2021, CC BY.

关键词： Convex optimization

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Real-Time Slip Detection using Tactile Information

Real-Time Slip Detection using Tactile Information

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IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

作者： Nabasmita Phukan Nayan M. Kakoty Manoj Sharma Department of Instrumentation Engineering Jorhat Engineering College Jorhat Assam INDIA Embedded System and Robotics Lab Tezpur University Assam INDIA

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Provably Convergent Federated Trilevel Learning

arXiv

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arXiv 2023年

作者： Jiao, Yang Yang, Kai Wu, Tiancheng Jian, Chengtao Huang, Jianwei Department of Computer Science and Technology Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University China Shanghai Research Institute for Intelligent Autonomous Systems China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China

Trilevel learning, also called trilevel optimization (TLO), has been recognized as a powerful modelling tool for hierarchical decision process and widely applied in many machine learning applications, such as robust neural architecture search, hyperparameter optimization, and domain adaptation. Tackling TLO problems has presented a great challenge due to their nested decision-making structure. In addition, existing works on TLO face the following key challenges: 1) they all focus on the non-distributed setting, which may lead to privacy breach;2) they do not offer any non-asymptotic convergence analysis which characterizes how fast an algorithm converges. To address the aforementioned challenges, this paper proposes an asynchronous federated trilevel optimization method to solve TLO problems. The proposed method utilizes µ-cuts to construct a hyper-polyhedral approximation for the TLO problem and solve it in an asynchronous manner. We demonstrate that the proposed µ-cuts are applicable to not only convex functions but also a wide range of non-convex functions that meet the µ-weakly convex assumption. Furthermore, we theoretically analyze the non-asymptotic convergence rate for the proposed method by showing its iteration complexity to obtain ϵ-stationary point is upper bounded by (Formula Presented). Extensive experiments on real-world datasets have been conducted to elucidate the superiority of the proposed method, e.g., it has a faster convergence rate with a maximum acceleration of approximately 80%. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce NAS Space for Heterogeneous Pipeline of CNNs

ExpoNAS: Using Exposure-based Candidate Exclusion to Reduce ...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Huijuan Duan Danghui Wang Xingting Zhao Kuizhi Mei Jihe Wang School of Computer Science Northwestern Polytechnical University Xi'an China Engineering Research Center of Embedded System Integration Ministry of Education Northwestern Polytechnical University Xi'an China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical University Xi'an China

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