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检索条件"机构=Center for AI and Robotics Department of Computer Engineering"

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A probabilistic roadmap based planning algorithm for wheeled-tip robots manipulating polygonal objects

A probabilistic roadmap based planning algorithm for wheeled...

引用

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

作者： N. Noori E. Noohi H. Moradi A. H. Bakhtiary M. Nili Ahmadabadi Robotics and AI Lab Control and Intelligent Processing Center Department of Electrical and Computer Engineering University of Tehran Tehran Iran

This work extends the probabilistic roadmap (PRM) framework by efficiently incorporating the force closure (FC) criterion into motion planning. A new FC verification approach is proposed that eliminates the need for testing FC in the intermediate configurations of the local planner. The algorithm is tested for special kinds of planar robots that have two wheeled-tip fingers. The wheels are actuated and can roll along the object's edges. We propose a general planning algorithm for this new mechanism without any limitations on the fingers structure and the task. The algorithm is implemented and the simulation results in ADAMS verify the validity of our algorithm.

关键词： Mobile robots Fingers Wheels Service robots Humanoid robots Intelligent robots Motion planning Testing Mechatronics Defense industry

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Fuzzy controller for cooperative object pushing with variable line contact

Fuzzy controller for cooperative object pushing with variabl...

引用

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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Reconfigurable disruption tolerant routing via reinforcement learning

Reconfigurable disruption tolerant routing via reinforcement...

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2009 International Joint Conference on Neural Networks, IJCNN 2009

作者： Kim, Tae-Hyung Pyeatt, Larry D. Wunsch II, Donald C. Applied Computational Intelligence Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409-0040 United States AI Robotics Laboratory Department of Computer Science Texas Tech. University Abilene TX 79601 United States

ISBN: (纸本)9781424435531

This paper shows packet delivery rate can be improved by adopting learning-based hybrid routing strategies when a wired network suffers from severe link disruption. The dynamics of the link disruptions complicate the routing problem;successful and stable routing operations of conventional routing approaches are hindered as the level of disruption increases. The target is to develop a robust and efficient routing approach in a single structure. A robust routing approach means a packet should be delivered to a destination even under severe disruptions. Efficient routing should deliver a packet with the shortest path at no disruption. These goals should be achieved with the maximum utilization of preexisting network components and with the minimal human intervention once installed. Therefore, we chose a popular conventional routing scheme, Link State, and add-ons that can learn changing network environment. Our approach is to add a learning agent and a simple routing scheme to Link State in order to automatically select a better routing scheme at an arbitrary level of disruption. Markov Decision Process is employed to model this problem. The simulation results show robustness and packet delivery rate are increased up to 35% at acceptable cost of computational and architectural complexity even when Link State approach is close to be collapsed. © 2009 IEEE.

关键词： Markov processes

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Multi-robot pursuit with visibility constraints

Multi-robot pursuit with visibility constraints

引用

International International Symposium on computer and Information Sciences (ISCIS)

作者： Esra Kadioglu Urtis Nikolaos Papanikolopoulos Computer Engineering Department TOBB University of Economics and Technology Ankara Turkey Center of Distributed Robotics Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA

We address the problem of pursuing a moving target from multiple angles using multiple mobile robots. The pursuer uses a modified form of pursuit curve in order to reach the multiple aim points which are at a pre-determined distance and angle from the target. This is different from existing works that track a target to localize it, follow a target by keeping it in the current frame of view generally from behind the target, or pursue a target in order to establish a line of sight. The focus in our work is on an efficient pursuit of the target such that the pursuers move to a position in order to obtain certain task specific information or perform actions that require specific positioning with respect to the target. Examples include following a target and taking left, right, and frontal images of it for accurate identification, or robots approaching a vehicle for docking, etc. In this paper, we define the multi-angle pursuit problem for multiple robots and present a Pareto optimal solution for task allocation.

关键词： Mobile robots Target tracking Robot vision systems Cameras Cost function Robot sensing systems computer vision Distributed computing computer science Focusing

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Reconfigurable disruption tolerant routing via Reinforcement Learning

Reconfigurable disruption tolerant routing via Reinforcement...

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International Joint Conference on Neural Networks (IJCNN)

作者： Tae-Hyung Kim Larry D. Pyeatt Donald C. Wunsch Applied Computational Intelligence Laboratory Department of Electrical & Computer Engineering Missouri University of Science and Technology Rolla MO USA AI Robotics Laboratory Department of Computer Science Texas Tech University Abilene TX USA

This paper shows packet delivery rate can be improved by adopting learning-based hybrid routing strategies when a wired network suffers from severe link disruption. The dynamics of the link disruptions complicate the routing problem; successful and stable routing operations of conventional routing approaches are hindered as the level of disruption increases. The target is to develop a robust and efficient routing approach in a single structure. A robust routing approach means a packet should be delivered to a destination even under severe disruptions. Efficient routing should deliver a packet with the shortest path at no disruption. These goals should be achieved with the maximum utilization of preexisting network components and with the minimal human intervention once installed. Therefore, we chose a popular conventional routing scheme, link state, and add-ons that can learn changing network environment. Our approach is to add a learning agent and a simple routing scheme to link state in order to automatically select a better routing scheme at an arbitrary level of disruption. Markov decision process is employed to model this problem. The simulation results show robustness and packet delivery rate are increased up to 35% at acceptable cost of computational and architectural complexity even when link state approach is close to be collapsed.

关键词： Learning Robustness Disruption tolerant networking Internet Computational intelligence Laboratories Fault tolerance TCPIP Routing protocols Neural networks

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Speeding up top-down attention control learning by using full observation knowledge

Speeding up top-down attention control learning by using ful...

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： N. Noori M. Nili Ahmadabadi M. S. Mirian B. N. Araabi AI Lab Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424448081

We present a general mathematical description of the top-down attention control problem. Three important components are identified in the model: context extraction, attention focus and decision making. The context gives a coarse blurry representation of the whole input; the attention module models the focus of attention on a limited part of input, and the decision making component accounts the final decision of the agent for its motory actions. In order to achieve a faster convergence of attention learning in the online phase, an offline optimization step is performed in advance. To do so, we incorporate the knowledge of a full observer agent that has approximately learned the optimal decision making of the task. The simulation results show that by employing our algorithm, the learning speed is improved.

关键词： Context modeling Decision making Layout Focusing Convergence Information filtering Information filters Robot sensing systems Bayesian methods Humans

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Dynamic manipulation of active objects: Modeling and optimization

Dynamic manipulation of active objects: Modeling and optimiz...

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

作者： L. Makarem A. Akbarimajd M. Nili Ahmadabadi Robotics and AI Laboratory Control and Intelligent Processing Center of Exellence ECE Department University of Tehran Tehran Iran Faculty of Engineering University of Mohaghegh Ardabil Iran

In this paper the problem of dynamic manipulation of active objects by throwing is studied. Here active object means a multi-body object that can actively move its body parts. The prime reason for selecting this problem is existence of conceptual analogy between it and dynamic walking. The second reason is theoretical attraction in addition to its possible practical applications for manipulation of active objects in space or in micro scales. First the task is decomposed into three distinct phases and it is mathematically modeled. Main constraints such as requirement to hold dynamic grasp are also derived and mapped into the manipulator's configuration space. Then the task is formulated as an optimization problem and a proper cost function in the manipulator's configuration space is presented. Finally this optimization problem is solved for obtaining appropriate trajectories of manipulator's joints in addition to that of the active object. Simulation results in ADAMS verify the developed formulations.

关键词： Manipulator dynamics Legged locomotion Arm Intelligent robots Leg Mechatronics Mathematical model Cost function Orbital robotics Motion control

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Rut tracking and steering control for autonomous rut following

Rut tracking and steering control for autonomous rut followi...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Camilo Ordonez Oscar Y. Chuy Emmanuel G. Collins Xiuwen Liu Center for Intelligent Systems Control and Robotics Department of Mechanical Engineering Florida A&M University-Florida State University USA Center for Intelligent Systems Control and Robotics Department of Computer Science Florida State University Tallahassee FL USA

Ruts formed as a result of vehicle traversal on soft ground are used by expert off road drivers because they can improve vehicle safety on turns and slopes thanks to the extra lateral force they provide to the vehicle. In this paper we propose a rut detection and tracking algorithm for autonomous ground vehicles (AGVs) equipped with a laser range finder. The proposed algorithm utilizes an extended Kalman filter (EKF) to recursively estimate the parameters of the rut and the relative position and orientation of the vehicle with respect to the ruts. Simulation results show that the approach is promising for future implementation.

关键词： Land vehicles Road vehicles Vehicle safety Remotely operated vehicles Vehicle driving Force control Control systems Intelligent robots Mobile robots Vehicle detection

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Gait control of modular climbing caterpillar robot

Gait control of modular climbing caterpillar robot

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

作者： W. Wang H. X. Zhang K. Wang J. W. Zhang W. H. Chen Robotics Institute School of Mechanical Engineering and Automation Beijing Aeronautics and Astronautics University Beijing China Dept of Informatics University of Hamburg Beijing Germany Department of Computer Science University of Hamburg Hamburg Germany Robotics Institute Beijing University of Aeronautics and Astronautics Beijing China Center of Electrical and Electronics Engineering Beijing University of Aeronautics and Astronautics Beijing China

The concept of a modular climbing caterpillar robot is inspired by the kinematics of the real caterpillar. Due to the fixed constraints between the suckers and wall, the gait of the caterpillar robot engages a changing kinematic chain which is from an open chain to a closed chain, and then to an open chain orderly. This paper investigates the joint control methods of the gait in detail. During the open chain periods, an Unsymmetrical Phase Method (UPM) is applied to ensure the reliable attachment of the passive suckers to the wall. But in the closed chain state, a four links kinematics model is adopted to fulfill the fixed constraints produced by the attached suckers. By combining the two methods together, we acquire complete joint control trajectories for a modular caterpillar robot with seven joints. At the end of this paper, on-site tests confirm the above principles and the validity of the climbing gait.

关键词： Legged locomotion Kinematics Climbing robots robotics and automation Mobile robots Intelligent robots Mechanical engineering computer science Joining processes Tail

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Semi-parametric adaptive control of discrete-time nonlinear systems

Semi-parametric adaptive control of discrete-time nonlinear ...

引用

IEEE International Conference on Automation and Logistics

作者： Chenguang Yang Tianyou Chai Lianfei Zhai Shuzhi Sam Ge Tong Heng Lee Social Robotics Lab Interactive Digital Media Institute and Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Process Industry Automation Ministry of Education Research Center of Automation Northeastern University Shenyang China

In this paper, we investigate a novel adaptive design approach for nonlinear systems as an exploration of the new challenging topic on dealing with both parametric and nonparametric internal uncertainties in adaptive control of discrete-time nonlinear systems. The existence of both two kinds of uncertainties makes it very difficult or even impossible to apply the traditional recursive identification algorithms which are designed for parametric systems. To best utilize the existing adaptive control technique, a novel deadzone with threshold converging to zero has been proposed to modify the traditional gradient update law for parameters estimation, while an auxiliary output including both uncertainties is introduced to facilitate the nonparametric uncertainties compensation. It is rigorously proved that the designed adaptive control guarantees the boundedness of all the closed-loop signals and achieves asymptotic tracking performance.

关键词： Adaptive control Nonlinear systems Sampling methods Path planning Testing Automation Road accidents Genetic algorithms Unmanned aerial vehicles Ant colony optimization

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