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IEEE International Conference on robotics and Automation (ICRA)

作者： Chahat Deep Singh Riya Kumari Cornelia Fermüller Nitin J. Sanket Yiannis Aloimonos Perception and Robotics Group University of Maryland Institute for Advanced Computer Studies University of Maryland College Park MD USA Robotics Engineering Worcester Polytechnic Institute MA USA

In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various challenges such as scalability, cost efficiency and photorealism. To avoid expensive and strenuous dataset collection and annotations, researchers have inclined towards computer-generated datasets. However, a lack of photorealism and a limited amount of computer-aided data has bounded the accuracy of network predictions. To this end, we present WorldGen - an open source framework to automatically generate countless structured and unstructured 3D photorealistic scenes such as city view, object collection, and object fragmentation along with its rich ground truth annotation data. WorldGen being a generative model gives the user full access and control to features such as texture, object structure, motion, camera and lens properties for better generalizability by diminishing the data bias in the network. We demonstrate the effectiveness of WorldGen by evaluating deep optical flow. We hope such a tool can open doors for future research in a myriad of domains related to robotics and computer vision by reducing manual labor and cost for acquiring rich and high-quality data.

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OysterNet: Enhanced Oyster Detection Using Simulation

OysterNet: Enhanced Oyster Detection Using Simulation

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IEEE International Conference on robotics and Automation (ICRA)

作者： Xiaomin Lin Nitin J. Sanket Nare Karapetyan Yiannis Aloimonos Perception and Robotics Group University of Maryland Institute for Advanced Computer Studies University of Maryland College Park MD USA Robotics Engineering Worcester Polytechnic Institute MA USA

Oysters play a pivotal role in the bay living ecosystem and are considered the living filters for the ocean. In recent years, oyster reefs have undergone major devastation caused by commercial over-harvesting, requiring preservation to maintain ecological balance. The foundation of this preservation is to estimate the oyster density which requires accurate oyster detection. However, systems for accurate oyster detection require large datasets obtaining which is an expensive and labor-intensive task in underwater environments. To this end, we present a novel method to mathematically model oysters and render images of oysters in simulation to boost the detection performance with minimal real data. Utilizing our synthetic data along with real data for oyster detection, we obtain up to 35.1 % boost in performance as compared to using only real data with our OysterNet network. We also improve the state-of-the-art by 12.7%. This shows that using underlying geometrical properties of objects can help to enhance recognition task accuracy on limited datasets successfully and we hope more researchers adopt such a strategy for hard-to-obtain datasets.

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Improved Aerodynamic Performance of Ornithopter Aerial Robot Using Spatial Mechanism Compared to Planar Design

Improved Aerodynamic Performance of Ornithopter Aerial Robot...

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

作者： Sina Hallajian S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab K. N. Toosi University of Technology Tehran Iran

Ornithopter’s research can be categorized into two parts. First, aerodynamics analysis of the flying robot including designing the body and choosing the robot’s material based on the analysis. Second, design and analysis of the mechanism which makes the wings move. So far, most of the researches has been focused on the first subject, i. e., aerodynamics analysis; even some books were published on this topic. However, there is little research about the mechanisms while most of the previous works are based on the patterns verified before. This paper will propose the design of a new spatial mechanism. Besides, three common planar mechanisms will be modeled and simulated to analyze and compare to the proposed mechanism in terms of aerodynamics forces for one wing beat cycle. These results reveal that the proposed 3D mechanism works more promising than others.

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Trajectory Tracking of Robotic Arms Using Learning Modified Transpose Jacobian

Trajectory Tracking of Robotic Arms Using Learning Modified ...

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

作者： Danial Ansari S Ali A Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics & Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran Iran

In this research, the issue of trajectory tracking in task space of a robotic arm with rotational joints has been solved. For this purpose, a non-model based controller the modified jacobian-transpose is used which it’s performance has been improved by reinforcement learning. Traditionally, the settings of the error thresholds for this controller will require trial and error, but in this algorithm, reinforcement learning is used to adjust these parameters online and according to the conditions. The simulations for the desired trajectory indicate that the improvement of the trajectory tracking achieved by using proposed algorithm. Also, the superiority of this controller in noisy conditions compared to the reference Jacobian transpose controller has been shown.

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Multi-aspect Optimal Sliding Mode Controller for a Mecanum Wheeled Robot

Multi-aspect Optimal Sliding Mode Controller for a Mecanum W...

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

作者： Sohrab Allahyari Hamid Rahmanei S. Ali A. Moosavian Dept. of Mechanical Engineering Center of Excellence in Robotics & Control Advanced Robotics & Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran

Four-wheel drive Mecanum robots have gained attention due to their ability to move in all directions, which allows them to work in tight and complex environments. For this reason, ensuring precise control of these robots along predefined trajectories is crucial. This work presents a comparative study on the effects of parametric uncertainties, external disturbances, measurement noises, and initial deviations on the trajectory-tracking performance of a 4-wheel drive Mecanum robot. First, the kinematic and kinetic models of the Mecanum robot are introduced. Then, the integral sliding mode control is designed, and proof of stability is provided. In addition, we explore other control strategies, including PID, feedback linearization, sliding mode, and adaptive sliding mode control, that are designed for this robot. Furthermore, the particle swarm optimization algorithm is hired for the controllers with a cost function as the total sum of average error, maximum error, and final error. Optimization has been done on all controllers to compare the results fairly. To appraise the effectiveness of the proposed control optimization methods, simulations are carried out in MATLAB/Simulink. The results reveal that the proposed ISMC method performs best in both defined scenarios compared to other controllers. However, it must be noted that the ISMC controller exhibits limitations when facing significant uncertainties in the dynamic model. This study underscores the effectiveness of our proposed control method and provides valuable insights into the practical implementation controller for the Mecanum robot in real-world applications.

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Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

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engineering 2022年第10期17卷 232-243页

作者： Zihang Gao Guanglu Jia Hongzhao Xie Qiang Huang Toshio Fukuda Qing Shi Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China

Existing biomimetic robots can perform some basic rat-like movement primitives(MPs)and simple behavior with stiff combinations of these *** mimic typical rat behavior with high similarity,we propose parameterizing the behavior using a probabilistic model and movement ***,an analysis of fifteen 10 min video sequences revealed that an actual rat has six typical behaviors in the open field,and each kind of behavior contains different bio-inspired combinations of eight *** used the softmax classifier to obtain the behavior-movement hierarchical probability ***,we specified the MPs using movement parameters that are static and *** obtained the predominant values of the static and dynamic movement parameters using hierarchical clustering and fuzzy C-means clustering,*** predominant parameters were used for fitting the rat spinal joint trajectory using a second-order Fourier series,and the joint trajectory was generalized using a back propagation neural network with two hidden ***,the hierarchical probability model and the generalized joint trajectory were mapped to the robot as control policy and commands,*** implemented the six typical behaviors on the robot,and the results show high similarity when compared with the behaviors of actual rats.

关键词： Biomimetic Bio-inspired robot Neural network learning system Behavior generation

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Comprehensive and Gamified Rehabilitation System for Upper-Limb Impairment Treatments

Comprehensive and Gamified Rehabilitation System for Upper-L...

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

作者： Vahid Yazdnian Ali Delavari Hadi Moradi Siavash Shams Mahdi Teymouri Abolfazl Rezaei Advanced Robotics Laboratory School of ECE College of Engineering University of Tehran

ISBN: (纸本)9781665454537

There are several major barriers in the rehabilitation process, such as transportation problems, the repetitive nature of traditional rehabilitation exercises, and lack of motivation, also some difficulties in managing a center for this purpose. The objective of this paper is to present a comprehensive rehabilitation system in order to mitigate and obviate some of these major problems. We have developed a Human-Computer Interaction form of treatment, using gamification methods and a low-cost, efficient, and specific movement data acquisition system so as to motivate patients to increase their movement domain and help them to find practices more exciting. We have implemented four different games specifically designed for rehabilitation purposes to be effective in the recovery procedure and to be visually attractive for patients. In addition, we have presented a well-organized software for patients’ management purposes and tracking their recovery procedure via pertinent diagrams. More importantly, while other previous gamified systems are suffering from fake movements by patients in order to accomplish their game achievements, we have provided a method to prevent this very effectively. Ultimately, we performed an experiment on 12 patients with upper limb impairment to assess the effectiveness of our system. The result of the questionnaire shows that almost all of the patients stated the efficacy of this system in all claimed areas. Moreover, the study revealed a favorable increase in patients’ movement domain using the system and practically illustrated the frequency of non-relevant joint utilization by patients during practices.

关键词： Training Video games Tracking Transportation Games Medical services Production

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Low Power Coherent Ising Machine Based on Mechanical Kerr Nonlinearity

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Physical Review Letters 2023年第7期130卷 073802-073802页

作者： Yoonhyuk Rah Youngjae Jeong Sangyoon Han Kyoungsik Yu School of Electrical Engineering Korea Advanced Institute of Science and Technology KAIST Daejeon 34141 Republic of Korea Robotics and Mechatronics Engineering Daegu-Gyeongbuk Institute of Science and Technology DGIST Daegu 42988 Republic of Korea

Finding a reliable Ising machine for solving nondeterministic polynomial-class problems has attracted great attention in recent years, where an authentic system can be expanded with polynomial-scaled resources to find the ground state Ising Hamiltonian. In this Letter, we propose an extremely low power optomechanical coherent Ising machine based on a new enhanced symmetry breaking mechanism and highly nonlinear mechanical Kerr effect. The mechanical movement of an optomechanical actuator induced by the optical gradient force greatly increases the nonlinearity by a few orders and significantly reduces the power threshold using conventional structures capable of fabrication via photonic integrated circuit platforms. With the simple but strong bifurcation mechanism and remarkably low power requirement, our optomechanical spin model opens a path for chip-scale integration of large-size Ising machine implementations with great stability.

关键词： Kerr effect Nanophotonics Nonlinear optics

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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1778-1791页

作者： Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni IEEE the School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing Ministry of EducationSun Yat-sen UniversityGuangzhou 510006China the School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China the State Key Laboratory of Robotics and Systems Harbin Institute of Technology(HIT)Harbin 150080China

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

关键词： Dual zeroing neural networks(ZNN) finite-time convergence model-free robot control robustness analysis

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A Soft Robotic Gripper with Active Palm for In-Hand Object Reorientation

arXiv

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arXiv 2023年

作者： Mack, Thomas Zhang, Ketao Althoefer, Kaspar The Centre for Advanced Robotics @ Queen Mary School of Engineering and Materials Science Queen Mary University of London United Kingdom

The human hand has an inherent ability to manipulate and re-orientate objects without external assistance. As a consequence, we are able to operate tools and perform an array of actions using just one hand, without having to continuously re-grasp objects. Emulating this functionality in robotic end-effectors remains a key area of study with efforts being made to create advanced control systems that could be used to operate complex manipulators. In this paper, a three fingered soft gripper with an active rotary palm is presented as a simpler, alternative method of performing in-hand rotations. The gripper, complete with its pneumatic suction cup to prevent object slippage, was tested and found to be able to effectively grasp and rotate a variety of objects both quickly and precisely. © 2023, CC BY.

关键词： Grippers

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