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International Conference on Neural Information Processing

作者： S.M. Eshgh M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rides for unseen situations. These benefits will be gained if the learning agents know the area of expertise and the expertness values of each other. In this paper, some Q-learning agents with different skills and expertness levels cooperate in learning. The agents use some criteria to judge others information and knowledge. Four expertness criterion, certainty and entropy measures are used to assign degrees of importance to others' Q-Tables. Effects of measuring these values based on their whole Q-Table, a portion of Q-Tables that reflects their proficiencies, and the states in Q-Tables on the learning quality are studied. Simple strategy sharing and two different weighted strategy-sharing methods are used to combine the acquired knowledge from different agents.

关键词： Intelligent robots Intelligent agent Process control control systems Intelligent control Laboratories Intelligent systems Physics Mathematics Entropy

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Trajectory tracking and obstacle avoidance of a ball and plate system using fuzzy theory

Trajectory tracking and obstacle avoidance of a ball and pla...

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Iranian Conference on Fuzzy Systems (IFSC)

作者： M. Ali Rastin Erfan Talebzadeh S. Ali A. Moosavian Mojtaba Alaeddin Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran Center of Excellence on Robotics and Control K. N. Toosi University of Technology Tehran Iran

Ball and plate platform is a nonlinear and underactuated plant. The plate is assumed to be the end-effector of a 3RRS parallel mechanism. By tilting the plate, the ball in opposite direction is pushed. The system of equation is achieved using Lagrange method. In this article, a fuzzy approach is proposed to control the ball on a given path. It consists of two level TS type fuzzy controller; the first level tries to lead the ball to the desired goal, and the second one prevents collision between the ball and obstacles.

关键词： Collision avoidance Trajectory Educational institutions Mathematical model Mechanical engineering Equations Robots

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A decision-making based approach for fault-handling in multi-agent systems

A decision-making based approach for fault-handling in multi...

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International Conference on Neural Information Processing

作者： M.S. Mirian M.N. Ahmadabadi Z. Navabi Robotics and AI Laboratory Department of Elect. and Comp. Eng Faculty of Engineering University of Tehran Iran Robotics and AI Lab Control & Intelligent Processing Center of Excellence Dept. of Elect. and Comp. Eng. University of Tehran Iran

This paper focuses on distributed fault recovery in agent-based systems by providing help for faulty members. In the presented method, if one faulty agent requests for help or agents are informed of fault in one of their teammates, they first decide if they are able to help or not. In the case that they are able to help and several help requests exist, helper agents specify a sequence of help actions through another distributed decision-making phase. The introduced fault clearing method is totally distributed in the sense that each helper agent makes its decisions by itself and no central or special agent exists in the system. In fact, the decision making process and the required information are designed such that the agents cooperate implicitly to prevent the system performance loss. The developed ideas are implemented in a simulated distributed control system. As it is shown, the proposed distributed fault-clearing method through reconfiguring the agents' roles is very effective.

关键词： Decision making Multiagent systems Robustness Condition monitoring Process control Robots Artificial intelligence Hardware Distributed decision making System performance

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A recomniender system based on invasive weed optimization algorithm

A recomniender system based on invasive weed optimization al...

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2007 IEEE Congress on Evolutionary Computation, CEC 2007

作者： Rad, Hoda Sepehri Lucas, Caro Robotics and Machine Intelligence Group School of Electrical and Computer Engineering University of Tehran P.O.Box: 11365 - 4563 Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran P.O. Box: 11365- 4563 Tehran Iran School of Cognitive Sciences IPM P.O. Box: 10395 - 5746 Tehran Iran

ISBN: (纸本)1424413400

Recommender systems intend to help users find their interested items from among a large number of items. We continue our previous work that emphasizes on "prioritized user-profile" approach as an effective approach to increase the quality of the recommendations. Prioritized user-profile is an approach that tries to implement more personalized recommendation by assigning different priority importance to each of the features of the user-profile for different users. In order to find the optimal priorities for each user an optimization algorithm is needed. In this paper, we employ a new optimization algorithm namely Invasive Weed Optimization (IWO) for this purpose. IWO is a relatively new and simple algorithm inspired from the invasive habits of growth of weeds in nature. Experimental results showed that IWO achieved the best accuracy in predicting users' interests compared to two other prioritized approaches which were based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) and to standard user-based Pearson algorithm on a movie dataset. © 2007 IEEE.

关键词： Genetic algorithms

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Modeling and Robust control of Ballbot Robot with Improved Power Transfer Mechanism

Modeling and Robust Control of Ballbot Robot with Improved P...

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

作者： Shamim kordbacheh Keivan baghestan Saeed shiri gheidary The Center of Excellence in Control and Robotics Amirkabir University of Technology Tehran Iran New Technologies Research Amirkabir University of Technology Tehran Iran Department of Mathematics and Computer Science Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9781728101286;9781728101279

In this paper, modeling and dynamic analysis and robust control of a Ballbot Robot are examined. Because these robots are under actuated, their control is more challenging than their counterparts, such as humanoid and Segway robots development of control theories for these robots is less taken into consideration and issues such as robust stability analysis less attention has been. One of the most significant issues in these robots is how to apply force to the ball. The omnidirectional wheels used in Ballbot have only one point of contact with the ball and practically limits the amount of force applied. To resolve this issue, students of Amirkabir University of Technology have designed a new omnidirectional wheel that increases the surface of the contact points of the ball and has caused more force on the ball before sliding and has improved the performance of the robot. For this reason, in this paper, taking into account the parametric uncertainty in dynamics, robust control algorithm is suggested. In addition, in order to show the performance of this controller, a PID controller is utilized to make a comparison. In the following, a robust stability analysis of linearization of the proposed control algorithm is undertaken based on Lyapunov's theory and it is shown the closed loop system is robust with suitable selection of gains. In the end, by presenting the simulation results obtained from the applying of the proposed control algorithm on a Ballbot Robot, the performance of the proposed control algorithm is evaluated.

关键词： Mobile robots Wheels Robot kinematics Mathematical model Kinetic energy Force

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Distributed formation control of networked mechanical systems

arXiv

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arXiv 2022年

作者： Javanmardi, Najmeh Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach. © 2022, CC BY.

关键词： Networked control systems

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Certainty and expertness-based credit assignment for cooperative Q-Learning agents with an AND-type task

Certainty and expertness-based credit assignment for coopera...

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International Conference on Neural Information Processing

作者： A. Harati M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence & AI and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In multiagent reinforcement learning, inter-agent credit assignment is a fundamental problem, since a single scalar reinforcement signal is the only reliable feedback that teams of learning agents receive. This problem is more critical in groups of independent learners with a joint task. In this research, it is assumed that a critic agent receives the environment feedback and assigns a proper credit to each agent using some measures. Three of such measures for a team of cooperative agents with a parallel and AND-type task are introduced. These measures somehow compare the agents' knowledge. One of these criteria, called normal expertness, is a non-relative measure while two other ones (certainty and relative normal expertness) are relative measure. It is experimentally shown that relative measures work better as they contain more information for the critic agent.

关键词： Feedback Intelligent agent Intelligent robots Process control control systems Intelligent control Artificial intelligence Robot kinematics Physics computing Reliability engineering

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A New Robust control for Mobile Robots with Differential Wheels: Output- and State- Dependent Riccati Equation Approach

A New Robust Control for Mobile Robots with Differential Whe...

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International Conference on control, Instrumentation, and Automation

作者： Neda Nasiri Ahmad Fakharian Mohammad Bagher Menhaj Dept. of Electrical Engineering Qazvin Branch Islamic Azad University Qazvin Iran Dept. of Electrical Engineering The Center of Excellence on Control and Robotics Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

A new application of Output- and State- Dependent Riccati Equation (OSDRE) framework for robust control of over-actuated uncertain systems with constraints is addressed in this paper. Towards this aim, an equivalent optimal problem is introduced using OSDRE. The performance index for an auxiliary output- and state- dependent system is modified through inclusion uncertainty upper bounds and then minimized. The proposed method is employed for controller design of a mobile robot with differential wheels. Uncontrollability condition put on SDRE due to differential constraints of wheels. This problem leads to SDRE to be hardly solved. One could overcome this problem by a proper coordinate transformation. In this paper considering the capability of output feedback to remove outer layer of kinematic and direct control the output dynamics, this problem is handled. Simulation results for a mathematical model and a wheeled mobile robot easily demonstrate the efficiency and satisfactory performance of the proposed robust control scheme.

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Learning distributed grasp in presence of redundant agents

Learning distributed grasp in presence of redundant agents

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： A.H. Elahibakhsh M. Nili Ahmadabadi F. Janabi-Sharifi B. Nadjar Araabi AI & Robotics Laboratory Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Eng. Institute for Studies on Theoretical Physics and Mathematics University of Tehran Tehran Iran Robotics and Manufacturing Automation Lab Department of Mechanical and Industrial Engineering Ryerson University Toronto ONT Canada

Learning distributed object grasp by a group of robots with redundant members is the main focus of this paper. In Elahibakhsh, A. H., et al. (2004), we tackled the problem of learning form closure grasp for planar convex objects by multiple non-communicating robots without any information about the shape of objects. In this paper, the problem in presence of redundant agents is investigated. Agents' states and actions are designed such that the group learns grasping different objects using Q-learning method. As the environment is not intelligent enough to assess each agent's effect on the team performance, a credit assignment algorithm based on knowledge evaluation is designed. The proposed method considers the environment credit for the team, number of redundant agents, and the expertness level of each agent in its credit assignment. Applicability of the designed approach is verified through a set of simulations. It is shown that the team learns grasping different objects. Therefore, it is expected that the proposed method can be extended for distributed grasp of deformable objects

关键词： Intelligent robots Learning Robot sensing systems Shape Cognitive robotics robotics and automation Intelligent agent Algorithm design and analysis Grasping Redundancy

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Extracting salient lines by Visual Attention for omnidirectional image classification

Extracting salient lines by Visual Attention for omnidirecti...

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IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP)

作者： AmirHossein Habibian Majid Nili-Ahmadabadi Babak Nadjar Araabi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences Tehran Iran

Representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene, which probably are useful in image classification. The proposed method is inspired from the Visual Attention, which is a perceptual mechanism in human and other primates that direct their perceptions to the limited regions of the scene. The attended regions are usually valuable in performing the task. Since the approach of using the lines to classify the images is particularly useful for omnidirectional images, we specialize our method to deal with these kinds of images. In the experiments, we demonstrate how our proposed methods improve the image classification performance with processing only small parts of the input images.

关键词： Feature extraction Visualization Image classification Gabor filters Image edge detection Histograms Computational modeling

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