/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

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Flow The Psychology Of Optimal Experience

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Biomechanics And Motor Control Of Human Movement

In this paper, an artificial neural network is proposed to estimate knee joint angle in hybrid activation of knee extension motion, including voluntary muscle contraction and functional electrical stimulation (FES) induced contraction. Voluntary electromyography (EMG) signals of three muscles responsible for knee extension and FES parameter which describe the FES intensity are used as input vector of the neural network, while the estimated knee angle is the output. During the experiment, FES with different combinations of parameters (pulse amplitude and pulse width) was delivered to the rectus femoris muscle of a healthy male subject when the knee was in a periodic extension motion by voluntary muscle contraction. Raw EMG signals of three muscles, parameters of FES as well as the actual knee angle were recorded. Totally, there were 52,233 and 17,420 sampling points corresponding to 261 and 87 seconds used to train and validate the neural network. The result shows the trained network has a satisfactory performance on knee joint angle estimation whose output well follows the curve of actual knee angle. Root mean square error between estimated angle and actual angle is employed to represent the estimation accuracy which is 5.07 degree according to the experimental data.

EMG-based estimation of knee joint angle under functional electrical stimulation using an artificial neural network

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2014/media/files/0344.pdf

Leader-Following Output Consensus in a Network of Linear Agents with Communication Noises

An autonomous helicopter with a vision system onboard to track ground targets can accomplish very important tasks like inspection and surveillance. The autonomous helicopter target tracking system is a interdisciplinary complex system. A typical autonomous helicopter target tracking system using vision sensors usually includes five major component: a navigation system, a flight controller, a active vision system, a target state estimator and a helicopter guidance law. In this paper, we focus on target state estimator and helicopter guidance law. It is assumed that the target moves on a flat ground, so the relative position between the target and the helicopter can be measured by a monocular vision system. Kalman filter is used to estimate the state of the target based on the vision measurements. A new guidance law inspired by velocity pursuit guidance and car-following control is proposed to guide the helicopter to follow the moving target. The tracking system is tested in a virtual reality environment and the results shows that the performance of the system is satisfied.

Tracking ground targets using an autonomous helicopter with a vision system

Nowadays, most industrial robots have been designed to be mechanically stiff with rigid link. When a robot with heavy payload is running in fast motions, the residual vibrations of the end-effector are primary caused by joint flexibility. Therefore, the flexibility of joint cannot be neglected. This paper presents a systematic approach to dynamic modeling and residual vibration mode analysis for an industrial robot with rigid links and flexible joints (RLFJ). First, the flexibility of the joint is modeled as a torsional spring and the dynamic equations for this robot are derived by using Lagrange's method. Then, to examine residual vibration properties of the system, numerical simulation is carried out. The following important conclusions are drawn from simulation results: (1) the proposed dynamic model can represent joint flexibility of industrial robot and the joint flexibility causes the residual vibration of the end-effector; (2) for a given RLFJ model, the residual vibration is mainly affected by the payload mass, path of the task and joint stiffness.

Dynamic modeling and vibration mode analysis for an industrial robot with rigid links and flexible joints

Autonomous navigation plays important role in mobile robots. In this paper, a navigation controller based on spiking neural networks (SNNs) for mobile robots is presented. The proposed target-reaching navigation controller, in which the reactive architecture is used, is composed of three sub-controllers: the obstacle-avoidance controller and the wall-following controller using spiking neural networks (SNNs), and the goal-reaching controller. The experimental results show that the navigation controller can control the mobile robot to reach the target successfully while avoiding the obstacle and following the wall to get rid of the deadlock caused by local minimum. The proposed navigation controller does not require accurate mathematical models of the environment, and is suitable to unknown and unstructured environment.

Zeng-Guang Hou

Papers

EMG-based estimation of knee joint angle under functional electrical stimulation using an artificial neural network

Leader-Following Output Consensus in a Network of Linear Agents with Communication Noises

Tracking ground targets using an autonomous helicopter with a vision system

Dynamic modeling and vibration mode analysis for an industrial robot with rigid links and flexible joints

A target-reaching controller for mobile robots using spiking neural networks