This paper investigates the problem of one-step ahead optimal active sensing strategy to minimise estimation errors with range-only measurements for non-manoeuvring target. The determinant of Fisher Information Matrix...
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ISBN:
(纸本)9789897583803
This paper investigates the problem of one-step ahead optimal active sensing strategy to minimise estimation errors with range-only measurements for non-manoeuvring target. The determinant of Fisher Information Matrix (FIM) is utilized as the objective function in the proposed optimisation problem since it quantifies the volume of uncertainty ellipsoid of any efficient estimator. In consideration of physical velocity and turning rate constraints, the optimal heading angle command that maximises the cost function is derived analytically. Simulations are conducted to validate the analytical findings.
The article deals with the issues of rational use of material and human resources of structural units of energy services of enterprises. Periodic statistics do not fully reflect dynamic processes. Forecasting should f...
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Localization is the problem of determining a robot39;s location in an environment. Monte Carlo Localization (MCL) is a method of solving this problem by using a partially observable Markov decision process to find t...
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ISBN:
(纸本)9728865600
Localization is the problem of determining a robot's location in an environment. Monte Carlo Localization (MCL) is a method of solving this problem by using a partially observable Markov decision process to find the robot's state based on its sensor readings, given a static map of the environment. MCL requires a model of each sensor in order to work properly. One of the most important sensors involved is the estimation of the robot's motion, based on its encoders that report what motion the robot has performed. Since these encoders are inaccurate, MCL involves using other sensors to correct the robot's location. Usually, a motion model is created that predicts the robot's actual motion, given a reported motion. The parameters of this model must be determined manually using exhaustive tests. Although an accurate motion model can be determined in advance, a single model cannot optimally represent a robot's motion in all cases. With a terrestrial robot the ground surface, slope, motor wear, and possibly tire inflation level will all alter the characteristics of the motion model. Thus, it is necessary to have a generalized model with enough error to compensate for all possible situations. However, if the localization algorithm is working properly, the result is a series of predicted motions, together with the corrections determined by the algorithm that alter the motions to the correct location. In this case, we demonstrate a technique to process these motions and corrections and dynamically determine revised motion parameters that more accurately reflect the robot's motion. We also link these parameters to different locations so that area dependent conditions, such as surface changes, can be taken into account. These parameters might even be used to identify surface changes by examining the various parameters. By using the fact that MCL is working, we have improved the algorithm to adapt to changing conditions so as to handle even more complex situations.
Three-dimensional (3D) point cloud understanding is important for autonomous robots. However, point clouds are normally irregular and discrete. It is challenging to obtain semantic information from them. In this paper...
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Three-dimensional (3D) point cloud understanding is important for autonomous robots. However, point clouds are normally irregular and discrete. It is challenging to obtain semantic information from them. In this paper, we present a method to build a dense semantic map, which utilizes both two-dimensional (2D) image labels and 3D geometric information. The dense point cloud is built by using a state-of-the-art RGB-D SLAM system. It is further segmented into meaningful clusters using a graph-based method. Then, image keyframes during the SLAM process are used to extract semantic image labels by a convolution neural network (CNN). Finally, these semantic labels are projected to the point cloud clusters to achieve a 3D dense semantic map. The effectiveness of our method is validated on a popular public dataset.
A measuring system-a multiphase flow meter is installed in oil wells. It consists of a set of sensors and a computer. The flow meter registers the following set of primary data. Oil is a very useful mineral. More than...
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This paper presents a novel 2R parallel mechanism used as alt-azimuth pedestal, i. e. a 2-DOF (degree-of-freedom) pedestal for supporting and rotating equipment about two perpendicular axes. Its active joints are two ...
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This paper presents a novel 2R parallel mechanism used as alt-azimuth pedestal, i. e. a 2-DOF (degree-of-freedom) pedestal for supporting and rotating equipment about two perpendicular axes. Its active joints are two sliders equipped with servo control on a circular rail. The synchronous and asynchronous motions of the two sliders lead to the azimuth (rotation about the vertical axis) and pitch (rotation about the horizontal axis) of the rotatable platform, respectively. The DOF computation and kinematics are dealt with firstly, and then the dynamic model of the 2R parallel mechanism is established by using the Lagrange equation. Eventually, a numerical simulation of the typical trajectory motion is carried out, and the actuating torque needed in the actuators for the trajectory tracking motion is worked out by employing the derived inverse dynamic equations, which is consistent with the result obtained from commercial software. This study lays a solid base for the further investigation and engineering implementation of the 2R parallel mechanism.
Considering the problem of trajectory planning of redundant degree of freedom in autonomous operation for excavating robot, a method of trajectory planning for periodic operation of autonomous excavating robot based o...
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Considering the problem of trajectory planning of redundant degree of freedom in autonomous operation for excavating robot, a method of trajectory planning for periodic operation of autonomous excavating robot based on time-jerk synthetic optimum was proposed in this paper. Through a kinematic model establishment and forward/inverse kinematics analysis for working mechanism, the trajectory planning based on Hermite interpolation method was carried out. Taking the time-jerk as objective function, a mathematical model of nonlinear programming under the inequality constraints was established, and Genetic Algorithm was used to find out the globally optimal solution. The rapidity and stability of working process of excavating robot is effectively enhanced and it has an important significance to realize the intelligentization of construction machinery.
This paper proposes an alternate interpretation of the traditional lookup table controller via the Center Average De- fuzzier (CAD) in Fuzzy Set Theory with a set of Disjoint Block Pulse Membership Functions (DBPMFs)....
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This paper proposes an alternate interpretation of the traditional lookup table controller via the Center Average De- fuzzier (CAD) in Fuzzy Set Theory with a set of Disjoint Block Pulse Membership Functions (DBPMFs). Further, a new Heaviside Search Algorithm (HSA) is also proposed to implement the Fuzzy Lookup Table controller (FLTC) in a more efficient way. The computation complexity of our new HSA is O(Sigma R-i), where R-i is the number of membership functions for i th input variable in FLTC. Whereas the average computational complexity in traditional Linear Search Algorithm (LSA) is O((Sigma R-i)/2). In comparison with LSA, the HSA also reduces the complexity of coding significantly in the same order as the comparison of computation complexities between HSA and LSA. The balancing of Inverted Pendulum System (IPS) is adopted as the benchmark to show the feasibility and efficiency of this new FLTC and HSA.
This article present the design and construction of a PID controller for direct current motors motion control in low-cost robotic applications. The reasons which led us to the make the proposal and design of the syste...
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A transmission line remote monitoring system combined with wireless sensor technology was designed, through the single-chip computer control to complete the system data from the collection to send all aspects of data ...
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ISBN:
(纸本)9781510873377
A transmission line remote monitoring system combined with wireless sensor technology was designed, through the single-chip computer control to complete the system data from the collection to send all aspects of data processing work. The icing monitoring system uses capacitive thickness detection sensors to collect data from multiple capacitance values and send the collected data to the control center processor through the serial port. The processor then processes the data and stores it on the SD card. in. Through the single-chip computer control to complete the system data from collection to send all aspects of data processing. The processor finishes the data transmission and connects with the GPRS communication module through the RS232 serial port. The automatic detection of ice thickness using the difference in resistance characteristics of air and ice, it is a new type of object surface ice coating thickness detection method. The utility model can be applied to real-time continuous automatic monitoring engineering application fields of high-pressure transmission lines and fixed towers, buildings or various equipment surfaces, suspension brackets, forest branches, and the like.
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