In this research, a self-driving bicycle is constructed and the balancing control using the handlebar is studied. The controller is designed based on a model which characterizes the bicycle's lateral dynamics unde...
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ISBN:
(纸本)9789897583803
In this research, a self-driving bicycle is constructed and the balancing control using the handlebar is studied. The controller is designed based on a model which characterizes the bicycle's lateral dynamics under speed variations. As the model can be decomposed into a convex combination of four linear subsystems with time-varying coefficients, the proposed controller also consists of a convex combination of four linear, full-state feedback controllers. It is proved that if the full-state feedback controllers satisfy a set of linear matrix inequalities, the bicycle can maintain its lateral stability regardless of speed changes. Both simulations and experiments verify that the proposed controller can achieve robust balancing performance under various operating conditions.
In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approa...
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ISBN:
(纸本)9789897583803
In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approach. We use separate deep neural networks to: detect the object on the image, estimate the center of the object, and estimate the translation and "in-place" rotation of the object. Then, we use geometrical relations on the image and the camera model to recover the full 6D object pose. As a result, we avoid the direct estimation of the object orientation defined in SO3 using a neural network. We propose the 4D-NET neural network to estimate translation and "in-place" rotation of the object. Finally, we show results on the images generated from the Pascal VOC and ShapeNet datasets.
The propose of this work is to extract different features from surface EMG signals of forearm muscles such as MAV, RMS, NZC, VAR, STD, PSD, and EOF's. Signals are acquired through 8 channels from "Myo Armband...
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ISBN:
(纸本)9789897583049
The propose of this work is to extract different features from surface EMG signals of forearm muscles such as MAV, RMS, NZC, VAR, STD, PSD, and EOF's. Signals are acquired through 8 channels from "Myo Armband" sensor that is placed in the forearm of the human being. Then, identification and classification of 5 types of movements are done, including open hand, closed hand, hand flexed inwards, out and relax position. Classification of the movement is performed through machine learning and data mining techniques, using two methods such as Feedforward Neural Networks and Support Vector Machines. Finally, an analysis is done to identify which features extracted from the sEMG signals and which classification method present the best results.
Artifacts like motion blur are a common problem for vision systems on mobile robots, especially when operating under low light conditions or when using high-resolution sensors. In this contribution we present a scheme...
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ISBN:
(纸本)9789896740009
Artifacts like motion blur are a common problem for vision systems on mobile robots, especially when operating under low light conditions or when using high-resolution sensors. In this contribution we present a scheme for estimating the degree of motion artifacts, especially motion blur, present in a stream of individual camera images. A single quality estimate is derived per frame using data from an inertial measurement unit. Considering limited image processing capacity of resource-constrained mobile robots, we show a number of data processing strategies that are based upon the idea of congestion control by adaptive image rejection.
The paper is aimed to the robust control of parametric uncertain linear plants in conditions of signal quantization with time delay and bounded external perturbations. State vector of control plant is unmeasured. Outp...
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ISBN:
(纸本)9789897581984
The paper is aimed to the robust control of parametric uncertain linear plants in conditions of signal quantization with time delay and bounded external perturbations. State vector of control plant is unmeasured. Output of control plant is measured only via quantizer with transport delay. control algorithm is based on consecutive compensator method. Proposed algorithm provides convergence of tracking error to the reference signal with prespecified accuracy for bounded time delay in quantizer. Limitations on value of delay providing stability of closed-loop system are obtained.
We have developed a navigation system for a mobile robot that enables it to autonomously return to a start point after completing a route. It works efficiently even in complex, low structured and populated indoor envi...
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ISBN:
(纸本)9789898111319
We have developed a navigation system for a mobile robot that enables it to autonomously return to a start point after completing a route. It works efficiently even in complex, low structured and populated indoor environments. A point-based map of the environment is built as the robot explores new areas;it is employed for localization and obstacle avoidance. Points corresponding to dynamical objects are removed from the map so that they do not affect navigation in a wrong way. The algorithms and results we deem more relevant are explained in the paper.
Our proposal is aimed at achieving reliable task allocation in physical multi-agent systems by means of introspection on their dynamics. This new approach is beneficial as it improves the way agents can coordinate wit...
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Our proposal is aimed at achieving reliable task allocation in physical multi-agent systems by means of introspection on their dynamics. This new approach is beneficial as it improves the way agents can coordinate with each other to perform the proposed tasks in a real cooperative environment. Introspection aims at including reliable physical knowledge of the controlled systems in the agents' decision-making. To that end, introspection on control-grounded capabilities, inspired by the agent metaphor, are used in the task utility/cost functions. Such control-grounded capabilities guarantee an appropriate agent-oriented representation of the specifications and other relevant details encapsulated in every automatic controller of the controlled systems. In particular, this proposal is demonstrated in the successful performing of tasks by cooperative mobile robots in a simulated robot soccer environment. Experimental results and conclusions are shown, stressing the relevance of this new approach in the sure and trustworthy attainment of allocated tasks for improving multi-agent performance.
In this paper, a novel controller is proposed and applied for high accuracy tracking trajectory in the workspace of robot manipulators in presence of uncertainties and external disturbances. Most of nonlinear controll...
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ISBN:
(纸本)9789897581984
In this paper, a novel controller is proposed and applied for high accuracy tracking trajectory in the workspace of robot manipulators in presence of uncertainties and external disturbances. Most of nonlinear controllers are based on the mathematical model of robot manipulator, but a lot of robotic systems do not have exact model. This novel approach which consists on designing an Integral Backstepping with Time Delay control (IBTDC) can estimate uncertainties and keep high tracking performance. The proposed controller is able to stabilize the robot system, and also to drive the trajectory tracking errors to converge in finite time. Furthermore, experimental results are given to illustrate the effectiveness of the proposed method applied to the 7-DOF ANAT robot arm.
The paper addresses the problem of errors-in-variables filtering, i.e. the optimal estimation of inputs and outputs from noisy observations. While the optimal solution is known for linear time-varying systems of known...
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ISBN:
(纸本)9789728865849
The paper addresses the problem of errors-in-variables filtering, i.e. the optimal estimation of inputs and outputs from noisy observations. While the optimal solution is known for linear time-varying systems of known parameterisation, this paper considers a suboptimal approach where only an approximated set of parameters is available. The proposed filter is derived by the means of joint state and parameter estimation using the extended Kalman filter approach which, in turn, leads to a coupled state-parameter estimation procedure. However, the resulting parameter estimates appear to be biased in the presence of input noise. The novel filter is compared with a previously proposed suboptimal filter.
This paper presents a robust terminal sliding mode control using the EMG signal. The application deals with an exoskeleton-upper limb system, used for rehabilitation. The considered system is a robot with one degree o...
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ISBN:
(纸本)9789897583803
This paper presents a robust terminal sliding mode control using the EMG signal. The application deals with an exoskeleton-upper limb system, used for rehabilitation. The considered system is a robot with one degree of freedom controlling the flexion/extension movement of the elbow. The different stages of the EMG signal extraction were presented. Then, a second order terminal sliding mode algorithm has been developed to control the exoskeleton-upper limb system. A Stability study is realized and a robustness analysis is done using Monte Carlo simulation in presence of parametric uncertainties. Simulation results are provided to prove performance and effectiveness of the second order terminal sliding mode algorithm when tracking the EMG signal extracted from the human arm.
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