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

作者： Ahmad Moori Javad Khoramdel 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

RoboEye is a spherical 3RRR parallel robot which has been developed for its high precision. It can provide high speeds, so can be used for fast tracking tasks. To this end, in this paper proper deep learning approaches are combined with classical control methods. Deep learning algorithms are employed to detect an object of interest among various ones in a monocular image, and then obtain an estimatation of the distance to the camera. So, simultaneous depth estimation, and object detection with a monocular camera for real time implementation is proposed here. For fast calculations, also to overcome manufacturing uncertainties, inverse kinematic equations are computed by a multi-layer perceptron (MLP) network based on real data. Finally, a classical PID controller can perform a fast tracking of the object.

关键词： Cameras Estimation Kinematics Mathematical model Object detection Robot vision systems

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RoboWalk Trajectory Planning Based on the Human Gait Prediction Using LSTM

RoboWalk Trajectory Planning Based on the Human Gait Predict...

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

作者： S. Ali. A. Moosavian Amin Kiani Vahid Akbari Mahdi Nabipour Sina Ghanaat 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)9781665420952

The increasing demand for rehabilitation robots alongside the complexity of such devices have made their designing procedure a challenging task. One of the challenges is generating a walking pattern for lower limb exoskeletons in such a way that tasks like load carrying or rehabilitation can be performed with minimum disturbance to the human normal gait. This paper presents a deep learning method to predict the next step of RoboWalk joint angle patterns using previous trajectories of former steps. Six different gait data from an individual are chosen as the learning and test dataset. The human joint trajectories during each of the six considered gaits and the augmented human-RoboWalk kinematic model are used to extract RoboWalk’s joint trajectories. The Long-Short-Term Memory (LSTM) network is then used for predicting the future trajectory and classifying the phase of walking. The accuracy for the prediction is about 98.5 percent and the overall error in all the gait modes is less than 5 degrees.

关键词： Legged locomotion Training Performance evaluation Trajectory planning Kinematics Rehabilitation robotics Trajectory

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RobcWalk: Conceptual and Optimal Design

RobcWalk: Conceptual and Optimal Design

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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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Kinematics Modeling of a Wheel-Based Pole Climbing Robot (UT-PCR)

Kinematics Modeling of a Wheel-Based Pole Climbing Robot (UT...

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IEEE International Conference on robotics and Automation (ICRA)

作者： A. Baghani M.N. Ahmadabadi A. Harati Robotics and AI Lab Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Iran

This paper is concerned with the derivation of the kinematics model of the University of Tehran-Pole Climbing Robot (UT-PCR). As the first step, an appropriate set of coordinates is selected and used to describe the state of the robot. Nonholonomic constraints imposed by the wheels are then expressed as a set of differential equations. By describing these equations in terms of the state of the robot an underactuated driftless nonlinear control system with affine inputs that governs the motion of the robot is derived. A set of experimental results are also given to show the capability of the UT-PCR in climbing a stepped pole.

关键词： Climbing robots Wheels Mobile robots Robot kinematics Road transportation Intelligent robots Inspection Cleaning Artificial intelligence Stability

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Learning Individual Skills and Team Behaviors for Distributed Object Pushing

Learning Individual Skills and Team Behaviors for Distribute...

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IEEE International Conference on Mechatronics and Automation

作者： Hossein Aminaiee Majid Nili Ahmadabadi Control and Intelligent Processing Center of Excellence Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper we discuss a learning approach to distributed object pushing. In the proposed approach, first the required individual skills for single-robot object pushing are learned using a fuzzy reinforcement learning method. Then, the robots learn how to coordinate their actions to push the object to the desired configuration cooperatively in a distributed manner. The proposed team-level learning benefits from the knowledge, which is in the form of a Q-table, that the agent has gained in its individual learning phase by a special design of reward signal and state-action representation. Each robot learns a threshold on its Q-value using a single state reinforcement learning method and pushes the object when the Q-value of its best action in the current state is above this threshold. The reward signal is designed based on the robots' Q-tables and no external critic is needed for learning cooperation. Simulation results show that the robots learn their individual skills and a cooperation protocol to push the object cooperatively

关键词： Robot kinematics Learning Protocols Robot control robotics and automation Intelligent robots Signal design Mechatronics Process control Intelligent control

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Fuzzy controller for cooperative object pushing with variable line contact

Fuzzy controller for cooperative object pushing with variabl...

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International Conference on Mechatronics (ICM)

作者： Mahsa Aliakbar Golkar Sarah Taghavi Namin Hossein Aminaiee Control and Intelligent Processing Center of Excellence Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Iran

Designing an appropriate cooperation protocol in multi-robot systems such as multi-robot object manipulation systems is a challenging task. In this paper designing and implementing a cooperation protocol between two robots pushing an object toward an arbitrary goal configuration is investigated. The proposed method benefits from task decoupling which simplifies the cooperation protocol design. Each robot gets its proper action from a particular fuzzy inference system independently. The fuzzy controllers outputs are low-level robot commands by which the need to a robot path planning algorithm is eliminated. Simulation results show that robots could push the object to the goal configuration cooperatively. Experiments have been conducted to approve the proposed system.

关键词： Fuzzy control Robot kinematics Protocols Fuzzy systems Electric variables control control systems Multirobot systems Path planning Inference algorithms Mobile robots

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Learning Distributed Object Pushing: Individual Learning and Distributed Cooperation Protocol

Learning Distributed Object Pushing: Individual Learning and...

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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hossein Aminaiee Majid Nili Ahmadabadi Control and Intelligent Processing Center of Excellence Robotics and AI Lab Department of Electrical and Computer Engineering University of Tehran Iran

In this paper we study learning in cooperative object pushing systems. The proposed approach is based on the idea of learning individual skills and then mapping the required cooperative behaviors on the learned skills. The control point for each individual robot is chosen so as to simplify the design of the reinforcement signal and reduce the role of delayed reward on individual learning in addition to make cooperative protocol simpler. A fuzzy Q-learning system for learning individual object pushing is proposed, together with a method for coordination among the robots to push the object cooperatively. The coordination method takes into account the dynamics of the object and the learned individual skills. The idea of the coordination protocol is based on the notion of ability and active regions defined in this paper. In effect, the cooperation protocol is mapped to a Q-value based policy. Simulation results supportively show that the robots learn individual and cooperative object pushing efficiently

关键词： Protocols Robot kinematics Intelligent robots Fuzzy systems Learning Friction control systems Artificial intelligence Robot control Fuzzy control

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Characteristics identification of continuum robots for exact modeling

Characteristics identification of continuum robots for exact...

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

作者： Mohammad Dehghani S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems Laboratory Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran

Continuum robots do not have any joint in contrast to traditional articulated robots. Instead, these robots can bend, twist and stretch their backbone, to shape desired configurations and end-effector position. Therefore, exact modeling of these robots is a challenging problem, particularly in spatial deformations. This paper suggests identification of some mechanical characteristics of the backbone of continuum robots, to achieve accurate results. The importance of identification of characteristics, such as undeformed shape and modulus of elasticity, will be discussed. Then, some methods to identify these characteristics are presented. Theory of Cosserat Rod will be introduced and used for modeling continuum robotic arms in this paper. Finally, the proposed approach is used for a given robot, and the model obtained based on the identified parameters will be validated by experimental results.

关键词： Robots Temperature measurement Elasticity

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Pursuit Formation control Scheme for Double-Integrator Multi-Agent Systems

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IFAC Proceedings Volumes 2014年第3期47卷 10054-10059页

作者： Hamed Rezaee Farzaneh Abdollahi The Center of Excellence on Control and Robotics Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Department of Electrical and Computer Engineering Concordia University Montreal Quebec Canada

Pursuit formation control of double-integrator Multi-Agent Systems (MASs) is considered in this paper. To achieve a formation, a hierarchical control scheme is proposed in two layers. In the first layer, in a leaderless architecture, each agent pursues another one in a cyclic topology to achieve a regular polygon formation around a centroid, namely, pursuit centroid, and in the second layer, the agents agree on a pursuit centroid around which they pursue each other. Despite existing cyclic pursuit approaches in the literature which are based on agents with kinematic models and constant forward speeds, the proposed approach is based on agents with double-integrator dynamics without speed constraints. Numerical simulations for a team of six agents confirm the accuracy of the proposed control scheme.

关键词： Formation control mobile agents double-integrators cyclic pursuit

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