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Collaborative turning and jumping control of a cyborg locust via sensory stimulation

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Collaborative turning and jumping control of a cyborg locust...

International Conference on Electrical, Control and Instrumentation engineering (ICECIE)

作者： Peng Liu Songsong Ma Shen Liu Yao Li Bing Li School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9781665449670

In this study, we describe the first-ever demonstration of the turning and jumping control of locusts based on electrical stimulation, which can realize a cyborg jumper. In terms of perception, walking distance, speed, payload, maneuverability, and adaptability to complex environments, cyborgs can reveal unmatchable advantages to insect-scale artificial robots. Herein, live locusts (Locusta migratoria) were selected as the study platform. Antennae and cercus stimulations using electrical pulses were applied to elicit the insect to turn and jump. We examined both the turning angle and the angular velocity by tuning the stimulus amplitude or frequency. It is found the turning rate induced by antenna stimulation can be graded. Besides, the stimulation of the cercus at the distal abdomen triggered the jump reliably. Moreover, the directional jumping control of the locust was achieved by the collaboration of turning and jumping control. Such results provide the potential to establish a more precise and more efficient model to develop a direction-controllable cyborg jumper.

关键词： Legged locomotion Wireless communication Protocols Insects Collaboration Electrical stimulation Turning

Crossbreeding in random forest

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arXiv 2021年

作者： Nadi, Abolfazl Moradi, Hadi Taheri, Khalil Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran11155-4563 Iran SKKU Suwon16419 Korea Republic of

Ensemble learning methods are designed to benefit from multiple learning algorithms for better predictive performance. The tradeoff of this improved performance is slower speed and larger size of ensemble learning systems compared to single learning systems. In this paper, we present a novel approach to deal with this problem in Random Forest (RF) as one of the most powerful ensemble methods. The method is based on crossbreeding of the best tree branches to increase the performance of RF in space and speed while keeping the performance in the classification measures. The proposed approach has been tested on a group of synthetic and real datasets and compared to the standard RF approach. Several evaluations have been conducted to determine the effects of the Crossbred RF (CRF) on the accuracy and the number of trees in a forest. The results show better performance of CRF compared to RF. © 2021, CC BY-NC-ND.

关键词： Learning systems

Joint Counting, Detection and Re-Identification for Multi-Object Tracking

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arXiv 2022年

作者： Ren, Weihong Wu, Denglu Cao, Hui Chen, Xi'ai Han, Zhi Liu, Honghai The School of Mechanical Engineering and Automation State Key Lab of Robotics and Systems Harbin Institute of Technology Shenzhen518055 China The Shenzhen Duorou Intelligent System Co. Ltd. Shenzhen518055 China The School of Electrical Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Beijing110169 China

The recent trend in 2D multiple object tracking (MOT) is jointly solving detection and tracking, where object detection and appearance feature (or motion) are learned simultaneously. Despite competitive performance, in crowded scenes, joint detection and tracking usually fail to find accurate object associations due to missed or false detections. In this paper, we jointly model counting, detection and re-identification in an end-to-end framework, named CountingMOT, tailored for crowded scenes. By imposing mutual object-count constraints between detection and counting, the CountingMOT tries to find a balance between object detection and crowd density map estimation, which can help it to recover missed detections or reject false detections. Our approach is an attempt to bridge the gap of object detection, counting, and re-Identification. This is in contrast to prior MOT methods that either ignore the crowd density and thus are prone to failure in crowded scenes, or depend on local correlations to build a graphical relationship for matching targets. The proposed MOT tracker can perform online and real-time tracking, and achieves the state-of-the-art results on public benchmarks MOT16 (MOTA of 79.7%), MOT17 (MOTA of 81.3%) and MOT20 (MOTA of 78.9%). Source code is available at https://***/weihong9/CountingMOT. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks

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arXiv 2022年

作者： Yang, Liu Yang, Simon X. Li, Yun Lu, Yinzhi Guo, Tan The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada

Traditional machine learning techniques have been widely used to establish the trust management systems. However, the scale of training dataset can significantly affect the security performances of the systems, while it is a great challenge to detect malicious nodes due to the absence of labeled data regarding novel attacks. To address this issue, this paper presents a generative adversarial network (GAN) based trust management mechanism for Industrial Wireless Sensor Networks (IWSNs). First, type-2 fuzzy logic is adopted to evaluate the reputation of sensor nodes while alleviating the uncertainty problem. Then, trust vectors are collected to train a GAN-based codec structure, which is used for further malicious node detection. Moreover, to avoid normal nodes being isolated from the network permanently due to error detections, a GAN-based trust redemption model is constructed to enhance the resilience of trust management. Based on the latest detection results, a trust model update method is developed to adapt to the dynamic industrial environment. The proposed trust management mechanism is finally applied to secure clustering for reliable and real-time data transmission, and simulation results show that it achieves a high detection rate up to 96%, as well as a low false positive rate below 8%. © 2022, CC BY.

关键词： Generative adversarial networks

An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks

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arXiv 2022年

作者： Yang, Liu Lu, Yinzhi Yang, Simon X. Zhong, Yuanchang Guo, Tan Liang, Zhifang The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada The State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China

Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs. Firstly, a fuzzy trust evaluation method is presented to transform the transmission evidences into trust values while effectively alleviating the trust uncertainty. And then, a K-Means based outlier detection scheme is proposed to further analyze plenty of trust values obtained via fuzzy trust evaluation or trust recommendation. It can discover the commonalities and differences among sensor nodes while improving the accuracy of outlier detection. Finally, we present an evolutionary game based secure clustering protocol to achieve a trade-off between security assurance and energy saving for sensor nodes when electing for the cluster heads. A sensor node which failed to be the cluster head can securely choose its own head by isolating the suspicious nodes. Simulation results verify that our secure clustering protocol can effectively defend the network against the attacks from internal selfish or compromised nodes. Correspondingly, the timely data transfer rate can be improved significantly. © 2022, CC BY.

关键词： Sensor nodes

Evacuation problem under the nuclear leakage accident

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arXiv 2021年

作者： Yao, Canqi Chen, Shibo Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

To handle the detrimental effects brought by leakage of radioactive gases at nuclear power station, we propose a bus based evacuation optimization problem. The proposed model incorporates the following four constraints, 1) the maximum dose of radiation per evacuee, 2) the limitation of bus capacity, 3) the number of evacuees at demand node (bus pickup stop), 4) evacuees balance at demand and shelter nodes, which is formulated as a mixed integer nonlinear programming (MINLP) problem. Then, to eliminate the difficulties of choosing a proper M value in Big-M method, a Big-M free method is employed to linearize the nonlinear terms of the MINLP problem. Finally, the resultant mixed integer linear program (MILP) problem is solvable with efficient commercial solvers such as CPLEX or Gurobi, which guarantees the optimal evacuation plan obtained. To evaluate the effectiveness of proposed evacuation model, we test our model on two different scenarios (a random one and a practical scenario). For both scenarios, our model attains executable evacuation plan within given 3600 seconds computation time. © 2021, CC BY-NC-SA.

关键词： Buses

Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots

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arXiv 2023年

作者： Dinkel, Holly Di, Julia Santos, Jamie Albee, Keenan Borges, Paulo Moreira, Marina Alexandrov, Oleg Coltin, Brian Smith, Trey Department of Aerospace Engineering The University of Illinois Urbana-Champaign UrbanaIL United States Department of Mechanical Engineering Stanford University StanfordCA United States Department of Physics Chalmers University of Technology Gothenburg Sweden Maritime and Multi-Agent Autonomy Group The Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Robotics and Autonomous Systems Group CSIRO Data61 BrisbaneQLD Australia Intelligent Robotics Group The NASA Ames Research Center Moffett FieldCA United States

Assistive free-flyer robots autonomously caring for future crewed outposts—such as NASA’s Astrobee robots on the International Space Station (ISS)—must be able to detect day-to-day interior changes to track inventory, detect and diagnose faults, and monitor the outpost status. This work presents a framework for multi-agent cooperative mapping and change detection to enable robotic maintenance of space outposts. One agent is used to reconstruct a 3D model of the environment from sequences of images and corresponding depth information. Another agent is used to periodically scan the environment for inconsistencies against the 3D model. Change detection is validated after completing the surveys using real image and pose data collected by Astrobee robots in a ground testing environment and from microgravity aboard the ISS. This work outlines the objectives, requirements, and algorithmic modules for the multi-agent reconstruction system, including recommendations for its use by assistive free-flyers aboard future microgravity outposts. © 2023, CC BY.

关键词： Space stations

Joint routing and charging problem of multiple electric vehicles: A fast optimization algorithm

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arXiv 2021年

作者： Yao, Canqi Chen, Shibo Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

Logistics has gained great attentions with the prosperous development of e-commerce, which is often seen as the classic optimal vehicle routing problem. Meanwhile, electric vehicle (EV) has been widely used in logistic fleet to curb the emission of green house gases in recent years. Thus, solving the optimization problem of joint routing and charging of multiple EVs is in a urgent need, whose objective function includes charging time, charging cost, EVs travel time, usage fees of EV and revenue from serving customers. This joint problem is formulated as a mixed integer programming (MIP) problem, which, however, is NP-hard due to integer restrictions and bilinear terms from the coupling between routing and charging decisions. The main contribution of this paper lies at proposing an efficient two-stage algorithm that can decompose the original MIP problem into two linear programming (LP) problems, by exploiting the exactness of LP relaxation and eliminating the coupled term. This algorithm can achieve a near-optimal solution in polynomial time. In addition, another variant algorithm is proposed based on the two-stage one, to further improve the quality of solution. Compared with the state-of-the-art algorithm, extensive simulations are implemented to validate the effectiveness of the proposed algorithm. © 2021, CC BY-NC-SA.

关键词： Electric vehicles

MTPA-based Haptic Feedback Controller for Master Manipulator in Minimally Invasive Surgery

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MTPA-based Haptic Feedback Controller for Master Manipulator...

IEEE International Conference on robotics and Biomimetics

作者： Wenda Zhao Jian Chen Yilun Hong Hongbin Liu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong China School of Biomedical Engineering and Imaging Sciences King's College London London UK

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Haptic feedback is critical for teleoperation in surgical robots, particularly in Natural Orifice Transluminal Endoscopic Surgery (NOTES). This paper introduces a haptic controller designed to enhance force generation efficiency and resolution, surpassing traditional motor control frameworks. We propose a Maximum Torque Per Ampere (MTPA)-based Field-Oriented Control (FoC) strategy for haptic kinesthetic feedback controller, optimizing the performance of a master manipulator's joint with a brushless DC (BLDC) motor under stalled and ultra-slow conditions. This approach enables a master manipulator with three degrees of freedom (DoF) for force feedback. Its effectiveness is validated through simulator and surgical trials, demonstrating improved haptic feedback in surgical applications.

关键词： Motor drives Torque Minimally invasive surgery Medical robotics Force feedback Orifices Manipulators Motors Haptic interfaces Adaptive control