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IEEE International Conference on robotics and Automation (ICRA)

作者： Zhijian Ren Jiahui Yang Suhan Kim Yi-Hsuan Hsiao Jeffrey Lang Yufeng Chen Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology (MIT) Cambridge MA USA

Flight is an energetically expensive task. While aerial insects can effortlessly fly through natural environments, achieving power autonomous flights in insect-scale robots remains a major challenge. In prior works, we developed soft-actuated insect-scale aerial robots that demonstrated unique capabilities such as in-flight collision recovery and somersaults. However, the soft dielectric elastomer actuators (DEAs) have low efficiency (< 20%) and require a high driving voltage (>600 V). These properties represent formidable obstacles for soft aerial robots to achieve power autonomous flights. In this work, we developed a 127 mg boost circuit that can convert a 7.7 V DC input into a 600 V and 400 Hz output for driving a 120 mg DEA. It has an equivalent capacitance and resistance of 20 nF and 5 $\mathbf{k}\Omega$ , respectively. The DEA is assembled into a 158 mg aerial robot, which can demonstrate liftoff while carrying the boost circuit as a payload. Although the robot remains tethered to an off-board power supply, this result represents a first step towards achieving power autonomy in soft aerial robots.

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Advanced Robotic Surveillance for Urban Air Quality Safety

Advanced Robotic Surveillance for Urban Air Quality Safety

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IEEE International Conference on Electro-Information Technology

作者： Guillaume Hansen James R. Benson Muhammad Rafay Danish Khoa Truong Xinrui Yu Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A.

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

This paper presents a multifunctional quadruped robot, specifically engineered for comprehensive air quality monitoring and emergency assistance. Designed to navigate through urban environments, the robot autonomously collects and transmits real-time air quality data to a centralized database. This interdisciplinary paper integrates robotics, environmental science, and emergency response protocols to propose novel solutions for smart city infrastructure, public health, and disaster management. Specifically, this research highlights the critical role that autonomous systems play in monitoring environmental conditions and advancing safety protocols. This research leverages a comprehensive array of sensors including CO2 (MH-Z19), particle (SDS 011), GPS (ADA 746), DHT 22, MQ 9, and ADS 1115 converter, each meticulously implemented to ensure precise environmental data collection and analysis. Furthermore, the integration of cutting-edge technologies such as Robot Operating System (ROS), .NET MAUI, Python, and MariaDB establishes a robust framework for seamless operation, data processing, and secure storage within the quadruped robot system.

关键词： Temperature sensors Protocols Robot sensing systems Dynamic scheduling Sensors Quadrupedal robots Servers

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Heading Control of a Long-Endurance Insect-Scale Aerial Robot Powered by Soft Artificial Muscles

Heading Control of a Long-Endurance Insect-Scale Aerial Robo...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yi-Hsuan Hsiao Suhan Kim Zhijian Ren YuFeng Chen Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology (MIT) Cambridge MA USA

Aerial insects demonstrate fast and precise heading control when they perform body saccades and rapid escape maneuvers. While insect-scale micro-aerial-vehicles (IMAVs) have demonstrated early results on heading control, their flight endurance and heading angle tracking accuracy remain far inferior to that of natural fliers. In this work, we present a long endurance sub-gram aerial robot that can demonstrate effective heading control during hovering flight. Through using a tilted wing stroke-plane design, our robot demonstrates a 10-second flight where it tracks a desired yaw trajectory with maximum and root-mean-square (RMS) error of $\boldsymbol{14.2^{\circ}}$ and $\boldsymbol{5.8}^{\mathrm{o}}$ . The new robot design requires 7% higher lift forces for enabling heading angle control, which creates higher stress on wing hinges and adversely influences robot endurance. To address this challenge, we developed novel 3-layered wing hinges that exhibit 1.82 times improvement of lifetime. With the new wing hinges, our robot demonstrates a 40-second hovering flight - the longest among existing sub-gram IMAVs. These results represent substantial improvement of flight capabilities in soft-actuated IMAVs, showing the potential of operating these insect-like fliers in cluttered natural environments.

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QUADFormer: Learning-based Detection of Cyber Attacks in Quadrotor UAVs

arXiv

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arXiv 2024年

作者： Wang, Pengyu Yang, Zhaohua Yang, Nachuan Wang, Zikai Li, Jialu Zhang, Fan Wang, Chaoqun Wang, Jiankun Meng, Max Q.-H. Shi, Ling Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The School of Control Science and Engineering Shandong University Shandong China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Department of Electrical and Computer Engineering The University of Alberta Canada

Safety-critical intelligent cyber-physical systems, such as quadrotor unmanned aerial vehicles (UAVs), are vulnerable to different types of cyber attacks, and the absence of timely and accurate attack detection can lead to severe consequences. When UAVs are engaged in large outdoor maneuvering flights, their system constitutes highly nonlinear dynamics that include non-Gaussian noises. Therefore, the commonly employed traditional statistics-based and emerging learning-based attack detection methods do not yield satisfactory results. In response to the above challenges, we propose QUADFormer, a novel Quadrotor UAV Attack Detection framework with transFormer-based architecture. This framework includes a residue generator designed to generate a residue sequence sensitive to anomalies. Subsequently, this sequence is fed into a transformer structure with disparity in correlation to specifically learn its statistical characteristics for the purpose of classification and attack detection. Finally, we design an alert module to ensure the safe execution of tasks by UAVs under attack conditions. We conduct extensive simulations and real-world experiments, and the results show that our method has achieved superior detection performance compared with many state-of-the-art methods. (Video1) Copyright © 2024, The Authors. All rights reserved.

关键词： Antennas

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions 23

Digital Twin Definition for Detecting Abnormal Perspiration ...

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23rd RoEduNet Conference: Networking in Education and research, RoEduNet 2024

作者： Vizitiu, Cristian Turcin, Ioan Dominey, Kevin Alexander Softic, Selver Dinculescu, Adrian-Catalin Bocanet, Vlad I. Dugan, Cosmin Moraru, Sorin-Aurel The Space Applications and Technologies Laboratory Institute of Space Science-Subsidiary of INFLPR Magurele Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Automatics and Information Technology Brasov Romania CAMPUS 02 University of Applied Sciences Department Automation Technology Graz Austria CAMPUS 02 University of Applied Sciences Department IT and Business Informatics Graz Austria Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Faculty of Industrial Engineering Department of Manufacturing Engineering Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (纸本)9798331540388

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation. © 2024 IEEE.

关键词： Physiological models

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Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions

arXiv

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arXiv 2023年

作者： Dai, Bolun Khorrambakht, Rooholla Krishnamurthy, Prashanth Gonçalves, Vinícius Tzes, Anthony Khorrami, Farshad Control/Robotics Research Laboratory Electrical & Computer Engineering Department Tandon School of Engineering New York University BrooklynNY11201 United States Electrical Engineering New York University Abu Dhabi Abu Dhabi129188 United Arab Emirates

Control barrier functions (CBFs) have been widely applied to safety-critical robotic applications. However, the construction of control barrier functions for robotic systems remains a challenging task. Recently, collision detection using differentiable optimization has provided a way to compute the minimum uniform scaling factor that results in an intersection between two convex shapes and to also compute the Jacobian of the scaling factor. In this paper, we propose a framework that uses this scaling factor, with an offset, to systematically define a CBF for obstacle avoidance tasks. We provide theoretical analyses of the continuity and continuous differentiability of the proposed CBF. We empirically evaluate the proposed CBF's behavior and show that the resulting optimal control problem is computationally efficient, which makes it applicable for realtime robotic control. We validate our approach, first using a 2D mobile robot example, then on the Franka-Emika research 3 (FR3) robot manipulator both in simulation and experiment. Index Terms-Robot safety, collision avoidance. © 2023, CC BY.

关键词： Robot applications

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Study of Helicopter Optimal Autorotation Landing Procedure in Tail Rotor Drive Failure

Study of Helicopter Optimal Autorotation Landing Procedure i...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

This paper investigates the optimal landing trajectory and control procedure when a helicopter undergoes autorotation due to tail rotor drive failure (TRDF), in which an optimal control methodology is proposed. First, a helicopter flight dynamics model with TRDF was developed. Then, the autorotation in TRDF was converted to be a nonlinear optimal control problem, solved by direct node collocation method and sequential quadratic programming algorithm. Finally, a model helicopter (Z11) with single main rotor and tail rotor was used to demonstrate the proposed approach. An optimal autorotation landing procedure in TRDF was determined accordingly. Results indicate that the airframe will immediately respond to the excess torque generated by the main rotor via yawing, sideslip and rolling when TRDF occurs. The pilot is recommended to shut down the engine and perform a series of critical operations to stabilize the violent yaw and roll movements. In addition, flight test data were used to validate the numerical simulations of autorotation landing. The proposed optimal control approach provides a useful tool to investigate helicopter TRDF autorotation landing procedure. © 2022 IEEE.

关键词： Helicopters

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Learning a Better Control Barrier Function

arXiv

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arXiv 2022年

作者： Dai, Bolun Krishnamurthy, Prashanth Khorrami, Farshad Control/Robotics Research Laboratory Electrical & Computer Engineering Department Tandon School of Engineering New York University BrooklynNY11201 United States

Control barrier functions (CBFs) are widely used in safety-critical controllers. However, constructing a valid CBF is challenging, especially under nonlinear or non-convex constraints and for high relative degree systems. Meanwhile, finding a conservative CBF that only recovers a portion of the true safe set is usually possible. In this work, starting from a "conservative" handcrafted CBF (HCBF), we develop a method to find a CBF that recovers a reasonably larger portion of the safe set. Since the learned CBF controller is not guaranteed to be safe during training iterations, we use a model predictive controller (MPC) to ensure safety during training. Using the collected trajectory data containing safe and unsafe interactions, we train a neural network to estimate the difference between the HCBF and a CBF that recovers a closer solution to the true safe set. With our proposed approach, we can generate safe controllers that are less conservative and computationally more efficient. We validate our approach on two systems: a second-order integrator and a ball-on-beam. © 2022, CC BY.

关键词： Controllers

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Optimal Landing of Tilt-rotor Aircraft after Engine Failure Considering Pilot Inherent Limitations

Optimal Landing of Tilt-rotor Aircraft after Engine Failure ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China College of Aeronautics Nanjing University of Aeronautics and Astronautics National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics Jiangsu Nanjing China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

An augmented longitudinal rigid-body model is developed with a set of algebra equations describing the controls in the cockpit and the differential equations describing the pilot inherent limitations. The landing procedure after one engine failure is formulated into a nonlinear optimal control problem. XV-15 tilt-rotor aircraft is taken as the sample for the demonstration of landing in one engine failure during short takeoff. The results show that the total power required, thrust coefficient, longitudinal flapping angle and optimal controls are more relatively gentle than the solutions without considering the pilot inherent limitations. Compared with the basic longitudinal rigid-body model, the optimal solutions involve more control information. © 2022 IEEE.

关键词： Differential equations

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Real-Time Imitation of Human Head Motions, Blinks and Emotions by Nao Robot: A Closed-Loop Approach

Real-Time Imitation of Human Head Motions, Blinks and Emotio...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Keyhan Rayati Amirhossein Feizi Alireza Beigy Pourya Shahverdi Mehdi Tale Masouleh Ahmad Kalhor Wing-Yue Geoffrey Louie Human and Robot Interaction Lab Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical Engineering Shahrood University of Technology Shahrood Iran Intelligent Robotics Laboratory Oakland University Michigan USA

This paper introduces a novel approach for enabling real-time imitation of human head motion by a Nao robot, with a primary focus on elevating human-robot interactions. By using the robust capabilities of the MediaPipe as a computer vision library and the DeepFace as an emotion recognition library, this research endeavors to capture the subtleties of human head motion, including blink actions and emotional expressions, and seamlessly incorporate these indicators into the robot’s responses. The result is a comprehensive framework which facilitates precise head imitation within human-robot interactions, utilizing a closed-loop approach that involves gathering real-time feedback from the robot’s imitation performance. This feedback loop ensures a high degree of accuracy in modeling head motion, as evidenced by an impressive R2 score of 96.3 for pitch and 98.9 for yaw. Notably, the proposed approach holds promise in improving communication for children with autism, offering them a valuable tool for more effective interaction. In essence, proposed work explores the integration of real-time head imitation and real-time emotion recognition to enhance human-robot interactions, with potential benefits for individuals with unique communication needs.

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