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

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

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

In this paper, the design procedure of the RoboWalk as a lower limb rehabilitation assisting robot is presented. First, a brief introduction of the robot is presented. There is a horizontal force component that is inevitably generated by the robot, and user may suffer from this. In order to overcome this problem, a dimensional optimization is performed to minimize this component, besides the required torque to be exerted by user at knee joint. To this end, a conceptual design of RoboWalk is described using the dimensions obtained by the aforementioned optimization. The detailed design is performed afterwards, and reasons for designing of each major element are discussed in detail. Finally, it is shown that this design is capable of fulfilling our goals and requirements using actuators with lower torque-speed specification.

关键词： Exoskeletons Force Legged locomotion Knee Torque Rails

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Simulation Analysis of Human-RoboWalk Augmented Model

Simulation Analysis of Human-RoboWalk Augmented Model

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

作者： Mohamad R. Mohamadi Vahid Akbari Omid Mahdizadeh Mahdi Nabipour S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

Exoskeletons are used in different applications including the area of physical therapy in order to facilitate the patient's exercises and as an assisting technology to assist the elderly carry out their ordinary activities. At the beginning of this paper, the RoboWalk assistive device is introduced. Before constructing the system, the performance of the device must be analyzed through different simulations. Hence, the dynamics of the human and RoboWalk are then obtained using the Newton-Euler (NE) and the Recursive Newton Euler Algorithm (RNEA). The obtained models are then augmented to the human model to estimate the RoboWalkjoint forces and torques, and those of the human model. then, RoboWalk is imported to the human model in Opensim software and the augmented model is obtained by defining some constraints and joint models. controllers are then designed for the human and Robo Walk in Opensim. In the next step, The NE and RNEA models are then compared to the models obtained from Opensim software using the same gait data. It is shown that the NE and RNEA methods match very closely and both of the models possess the same behavior as the Opensim model.

关键词： Mathematical model Robots Force Actuators Footwear Knee Dynamics

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RoboWalk Multiple-Sensor and Multipolar Data Fusion

RoboWalk Multiple-Sensor and Multipolar Data Fusion

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

作者： Omid Mahdizadeh Vahid Akbari S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology. Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

RoboWalk is a two-legged rehabilitation assisting robot, which helps users by carrying a portion of the weight. In this paper, we propose an algorithm to correct the attitude and position error by means of an Adaptive Root Square Unscented Kalman Filter. To this end, the IMU and encoders are used to determine the robot kinematic configuration, but since there is no solid connection between the ground and the feet, the sensor's data may not lead to exact positioning configuration. Therefore, a new approach for estimating the position of the feet and the seat is presented. The method is based on using the standing foot IMU, and related encoders to obtain the seat position. Then, the obtained result is compared to the seat IMU and correcting the position. Next, the corrected position and the swing leg encoders are used to obtain the swing foot position, which is compared to the corresponding IMU, to modify and yield all corrected positions. Describing the proposed method, it is then implemented, and the results will be discussed.

关键词： Mathematical model Robot sensing systems Estimation Robot kinematics Foot

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Weakly Aligned Feature Fusion for Multi-modal Object Detection

arXiv

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arXiv 2022年

作者： Zhang, Lu Liu, Zhiyong Zhu, Xiangyu Song, Zhan Yang, Xu Lei, Zhen Qiao, Hong The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100086 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China The Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China The Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Hong Kong The Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China

To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, depth, etc. However, multi-modal data often suffer from the position shift problem, i.e. the image pair is not strictly aligned, making one object has different positions in different modalities. For the deep learning method, this problem makes it difficult to fuse multi-modal features and puzzles the CNN training. In this paper, we propose a general multi-modal detector named Aligned Region CNN (AR-CNN) to tackle the position shift problem. Firstly, a region feature alignment module with adjacent similarity constraint is designed to consistently predict the position shift between two modalities and adaptively align the cross-modal region features. Secondly, we propose a novel RoI jitter strategy to improve the robustness to unexpected shift patterns. Thirdly, we present a new multi-modal feature fusion method, which selects the more reliable feature and suppresses the less useful one via feature re-weighting. Additionally, by locating bounding boxes in both modalities and building their relationships, we provide novel multi-modal labelling named KAIST-Paired. Extensive experiments on 2D and 3D object detection, RGB-T and RGB-D datasets demonstrate the effectiveness and robustness of our method. Copyright © 2022, The Authors. All rights reserved.

关键词： Object recognition

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Robust Impedance control for Dual User Haptic Training System

Robust Impedance Control for Dual User Haptic Training Syste...

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

作者： R. Heidari M. Motaharifar H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

In this paper, an impedance controller with switching parameters for a dual-user haptic training system is introduced. The trainer and the trainee are connected through their haptic consoles, and the trainee performs the surgical procedure on the environment. The trainer can intervene in the procedure by pressing a mechanical pedal; thus, the control parameters are switched to transfer the authority over the task from the trainee to the trainer. The stability of each subsystem and the closed-loop stability of the overall system are investigated. The simulation results verify the performance of the proposed controller.

关键词： Haptic interfaces Impedance Surgery Training Mathematical model Stability analysis Force

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Real-world Robot Reaching Skill Learning Based on Deep Reinforcement Learning

Real-world Robot Reaching Skill Learning Based on Deep Reinf...

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第32届中国控制与决策会议

作者： Naijun Liu Tao Lu Yinghao Cai Rui Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences

Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes which are complicated,unpredictable,and *** overcome the limitation of traditional programming method,in this paper,we apply deep reinforcement learning(DRL) method to train robot agent to obtain skill *** policy trained with DRL on real-world robot is time-consuming and costly,we propose a novel and simple learning paradigm with the aim of training physical robot ***,our method train a virtual agent in an simulated environment to reach random target position from random initial ***,virtual agent trajectory sequence obtained with the trained policy,is transformed to real-world robot command with coordinate transformation to control robot performing reaching *** show that the proposed method can obtain self-adaptive reaching policy with low training cost,which is of great benefits for developing intelligent and robust robot manipulation skill system.

关键词： Robot reaching skill learning deep reinforcement learning

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Path Planning for a UAV by Considering Motion Model Uncertainty

Path Planning for a UAV by Considering Motion Model Uncertai...

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

作者： Hossein Sheikhi Darani Ali Noormohammadi-Asl Hamid D. Taghirad Advanced Robotics and Automated System (ARAS) Industrial Control Center of Excellence (ICEE) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

The primary purpose of path planning for unmanned aerial vehicles (UAVs), which is a necessary prerequisite toward an autonomous UAV, is to guide the robot to the predefined target while the chosen path is optimized. This paper addresses the problem of path planning for an unmanned aerial vehicle in a 2D indoor environment, considering motion uncertainty. To cope with this challenge, the problem of motion planning is formulated in three parts. A vision-based extended Kalman Filter (EKF) is used to localize the UAV in the unstructured environment. To overcome motion uncertainty, the problem is modeled as a Markov decision problem (MDP). Finally, a novel dynamic feedback linearization based switching controller is proposed for point-to-point motion. Simulation and experimental results are given to show the effectiveness of the proposed path planning method in practice.

关键词： Robot kinematics Path planning Uncertainty Robot sensing systems Switches

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Skill Assessment Using Kinematic Signatures: Geomagic Touch Haptic Device

Skill Assessment Using Kinematic Signatures: Geomagic Touch ...

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

作者： N. S. Hojati M. Motaharifar H. D. Taghirad A. Malekzadeh Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran Faculty of Mathematics K.N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

The aim of this paper is to develop a practical skill assessment for some designed experimental tasks, retrieved from Minimally Invasive Surgery. The skill evaluation is very important in surgery training, especially in MIS. Most of the previous studies for skill assessment methods are limited in the Hidden Markov Model and some frequency transforms, such as Discrete Fourier transform, Discrete Cosine Transform and etc. In this paper, some features have been extracted from time-frequency analysis with the Discrete Wavelet Transform and temporal signal analysis of some kinematic metrics which were computed from Geomagic Touch kinematic data. In addition, the k-nearest neighbors classifier are employed to detect skill level based on extracted features. Through cross-validation results, it is demonstrated that the proposed methodology has annrouriate accuracy in skill level detection.

关键词： Feature extraction Measurement Discrete wavelet transforms Haptic interfaces Surgery Microsoft Windows

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An event-based, digital time difference encoder model implementation for neuromorphic systems

TechRxiv

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TechRxiv 2020年

作者： Gutierrez-Galan, Daniel Schoepe, Thorben Dominguez-Morales, Juan P. Jimenez-Fernandez, Angel Chicca, Elisabetta Linares-Barranco, Alejandro The Robotics and Technology of Computers Lab Universidad de Sevilla Spain The SCORE Lab I3US Universidad de Sevilla Spain The Faculty of Technology and Cognitive Interaction Technology Center of Excellence Bielefeld University Germany The Bio-Inspired Circuits and Systems Lab Zernike Institute for Advanced Materials University of Groningen Netherlands The Groningen Cognitive Systems and Materials Center University of Groningen Nijenborgh 4 GroningenNL-9747 AG Netherlands

Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such systems. Furthermore, the event-based signal processing approach can be exploited for reducing the computational load and avoiding data loss, thanks to its inherently sparse representation of sensed data and adaptive sampling time. In event-based systems, the information is commonly coded by the number of spikes within a specific temporal window. However, event-based signals may contain temporal information which is complex to extract when using rate coding. In this work, we present a novel digital implementation of the model, called Time Difference Encoder, for temporal encoding on event-based signals, which translates the time difference between two consecutive input events into a burst of output events. The number of output events along with the time between them encodes the temporal information. The proposed model has been implemented as a digital circuit with a configurable time constant, allowing it to be used in a wide range of sensing tasks which require the encoding of the time difference between events, such as optical flow based obstacle avoidance, sound source localization and gas source localization. This proposed bio-inspired model offers an alternative to the Jeffress model for the Interaural Time Difference estimation, validated with a sound source lateralization proof-of-concept. The model has been simulated and implemented on an FPGA, requiring 122 slice registers of hardware resources and less than 1 mW of power consumption. © 2020, CC BY-NC-SA.

关键词： Signal encoding

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Kinematics and Dynamics Modeling of Spherical Parallel Manipulator

Kinematics and Dynamics Modeling of Spherical Parallel Manip...

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

作者： Omid Mahdizadeh Afshin Zeinaddini Meymand Mojtaba Mollahossein S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781728101286;9781728101279

Spherical parallel manipulators have been proposed for accurate and fast performance. In this paper, kinematics and dynamics of a spherical three degrees-of-freedom parallel manipulator are studied. First, both direct and inverse kinematics are solved by using a new geometric approach and defining a new appropriate set of coordinates. Then, based on the derived kinematics equations and Jacobian matrices of links, according to Lagrange method, the explicit dynamics formulation of the manipulator is developed. The obtained dynamics has been verified by using *** and MATlab Software, simultaneously. This explicit verified model is highly important to design and implement various model based control algorithms. So, a Fuzzy Adaptive PID controller is designed to show the controller's operation on the manipulator. Discussing the obtained results reveal the merits and importance of the proposed modeling.

关键词： Manipulator dynamics Kinematics Mathematical model Jacobian matrices Gravity Dynamics

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