2017, 26(3): 285-291.
doi: 10.15918/j.jbit1004-0579.201726.0301
摘要：
To solve the inverse kinematics problem for redundant degrees of freedom (DOFs) manipulators has been and still continues to be quite challenging in the field of robotics. Aiming at trajectory planning for a 7-DOF space manipulator system, joint rotation trajectories are obtained from predetermined motion trajectories and poses of the end effector in Cartesian space based on the proposed generalized inverse kinematics method. A minimum norm method is employed to choose the best trajectory among available trajectories. Numerical simulations with the 7-DOF manipulator show that the proposed method can achieve the planned trajectory and pose under the circumstances of minimum angular velocities. Moreover, trajectory results from the proposed kinematics model and inverse kinematics method has the advantages of simple modelling, low computation cost, easy to solve and plan trajectory conveniently. The smooth and continuous joint rotation functions obtained from the proposed method are suitable for practical engineering applications.
To solve the inverse kinematics problem for redundant degrees of freedom (DOFs) manipulators has been and still continues to be quite challenging in the field of robotics. Aiming at trajectory planning for a 7-DOF space manipulator system, joint rotation trajectories are obtained from predetermined motion trajectories and poses of the end effector in Cartesian space based on the proposed generalized inverse kinematics method. A minimum norm method is employed to choose the best trajectory among available trajectories. Numerical simulations with the 7-DOF manipulator show that the proposed method can achieve the planned trajectory and pose under the circumstances of minimum angular velocities. Moreover, trajectory results from the proposed kinematics model and inverse kinematics method has the advantages of simple modelling, low computation cost, easy to solve and plan trajectory conveniently. The smooth and continuous joint rotation functions obtained from the proposed method are suitable for practical engineering applications.
2018, 27(4): 630-636.
doi: 10.15918/j.jbit1004-0579.17140
摘要：
A novel convolutional neural network based on spatial pyramid for image classification is proposed. The network exploits image features with spatial pyramid representation. First, it extracts global features from an original image, and then different layers of grids are utilized to extract feature maps from different convolutional layers. Inspired by the spatial pyramid, the new network contains two parts, one of which is just like a standard convolutional neural network, composing of alternating convolutions and subsampling layers. But those convolution layers would be averagely pooled by the grid way to obtain feature maps, and then concatenated into a feature vector individually. Finally, those vectors are sequentially concatenated into a total feature vector as the last feature to the fully connection layer. This generated feature vector derives benefits from the classic and previous convolution layer, while the size of the grid adjusting the weight of the feature maps improves the recognition efficiency of the network. Experimental results demonstrate that this model improves the accuracy and applicability compared with the traditional model.
A novel convolutional neural network based on spatial pyramid for image classification is proposed. The network exploits image features with spatial pyramid representation. First, it extracts global features from an original image, and then different layers of grids are utilized to extract feature maps from different convolutional layers. Inspired by the spatial pyramid, the new network contains two parts, one of which is just like a standard convolutional neural network, composing of alternating convolutions and subsampling layers. But those convolution layers would be averagely pooled by the grid way to obtain feature maps, and then concatenated into a feature vector individually. Finally, those vectors are sequentially concatenated into a total feature vector as the last feature to the fully connection layer. This generated feature vector derives benefits from the classic and previous convolution layer, while the size of the grid adjusting the weight of the feature maps improves the recognition efficiency of the network. Experimental results demonstrate that this model improves the accuracy and applicability compared with the traditional model.
2016, 25(4): 502-511.
doi: 10.15918/j.jbit1004-0579.201625.0408
摘要：
Parking is an important and indispensable skill for drivers. With rapid urban development, the automatic parking assistant system is one of the key components in future automobiles. Path planning is always essential for solving parking problems. In this paper, a path planning method is proposed for parking using straight lines and circular curves of different radius without collisions with obstacles. The parking process is divided into two steps in which the vehicle reaches the goal state through the intermediate state from the initial state. The intermediate state will be selected from the intermediate state set with a certain criterion in order to avoid obstacles. Similarly, an appropriate goal state will be selected based on the size of the parking lot. In addition, an automatic parking system is built, which effectively achieves the parking lot perception, path planning and performs parking processes in the environment with obstacles. The result of simulations and experiments demonstrates the feasibility and practicality of the proposed method and the automatic parking system.
Parking is an important and indispensable skill for drivers. With rapid urban development, the automatic parking assistant system is one of the key components in future automobiles. Path planning is always essential for solving parking problems. In this paper, a path planning method is proposed for parking using straight lines and circular curves of different radius without collisions with obstacles. The parking process is divided into two steps in which the vehicle reaches the goal state through the intermediate state from the initial state. The intermediate state will be selected from the intermediate state set with a certain criterion in order to avoid obstacles. Similarly, an appropriate goal state will be selected based on the size of the parking lot. In addition, an automatic parking system is built, which effectively achieves the parking lot perception, path planning and performs parking processes in the environment with obstacles. The result of simulations and experiments demonstrates the feasibility and practicality of the proposed method and the automatic parking system.
2017, 26(2): 267-275.
doi: 10.15918/j.jbit1004-0579.201726.0217
摘要：
To investigate wavelength response of the no core fiber(NCF)interference spectrum to concentration, a three-layer back propagation(BP) neural network model was established to optimize the concentration sensing data. In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network, so that the accuracy of the measurement system was optimized. The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network, and the corresponding actual concentration value was used as the output value of the network, and the optimal network structure was trained. This paper discovers a preferable correlation between the predicted value and the actual value, where the former is approximately equal to the latter. The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94; similarly, correlations of 0.999 51 and 1.018 8 for a glucose concentration were observed. The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.
To investigate wavelength response of the no core fiber(NCF)interference spectrum to concentration, a three-layer back propagation(BP) neural network model was established to optimize the concentration sensing data. In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network, so that the accuracy of the measurement system was optimized. The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network, and the corresponding actual concentration value was used as the output value of the network, and the optimal network structure was trained. This paper discovers a preferable correlation between the predicted value and the actual value, where the former is approximately equal to the latter. The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94; similarly, correlations of 0.999 51 and 1.018 8 for a glucose concentration were observed. The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.
2016, 25(1): 71-76.
doi: 10.15918/j.jbit1004-0579.201625.0111
摘要：
In order to overcome the shortcomings of the previous obstacle avoidance algorithms, an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed. The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator. The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning. A 7-DOF manipulator was used in the simulation, and the results verified the effectiveness of the algorithm.
In order to overcome the shortcomings of the previous obstacle avoidance algorithms, an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed. The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator. The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning. A 7-DOF manipulator was used in the simulation, and the results verified the effectiveness of the algorithm.
2016, 25(2): 218-224.
doi: 10.15918/j.jbit1004-0579.201625.0209
摘要：
In order to observe the change and fluctuation in flow and pressure of a hydraulic quadruped robot's hydraulic system when the robot walks on trot gait, a co-simulation method based on ADAMS and AMESim is proposed. Firstly, the change rule in each swing angle of the hydraulic quadruped robot's four legs is analyzed and converted to the displacement change of the hydraulic cylinder by calculating their geometric relationship. Secondly, the robot's dynamic model is built in ADAMS and its hydraulic and control system models are built in AMESim. The displacement change of the hydraulic cylinder in the hydraulic system is used as the driving function of the dynamics model in ADAMS, and the driving force of the dynamics model is used as the loads of the hydraulic system in AMESim. By introducing the PID closed-loop control in the control system, the co-simulation between hydraulic system and mechanical system is implemented. Finally, the curve of hydraulic cylinders' loads, flow and pressure are analyzed and the results show that they fluctuate highly in accordance with the real situation. The study provides data support for the development of a hydraulic quadruped robot's physical prototype.
In order to observe the change and fluctuation in flow and pressure of a hydraulic quadruped robot's hydraulic system when the robot walks on trot gait, a co-simulation method based on ADAMS and AMESim is proposed. Firstly, the change rule in each swing angle of the hydraulic quadruped robot's four legs is analyzed and converted to the displacement change of the hydraulic cylinder by calculating their geometric relationship. Secondly, the robot's dynamic model is built in ADAMS and its hydraulic and control system models are built in AMESim. The displacement change of the hydraulic cylinder in the hydraulic system is used as the driving function of the dynamics model in ADAMS, and the driving force of the dynamics model is used as the loads of the hydraulic system in AMESim. By introducing the PID closed-loop control in the control system, the co-simulation between hydraulic system and mechanical system is implemented. Finally, the curve of hydraulic cylinders' loads, flow and pressure are analyzed and the results show that they fluctuate highly in accordance with the real situation. The study provides data support for the development of a hydraulic quadruped robot's physical prototype.
2016, 25(4): 526-532.
doi: 10.15918/j.jbit1004-0579.201625.0411
摘要：
Based on the multiple surface and fixed undirected communication topology, the adaptive leader follower control for multiple quadrotors is discussed. Our approach is based on leader follower architecture. Multiple surface control (MSC) is used to design consensus controller to make multiple quadrotors construct a formation during flying with the presence of uncertainty item caused by the ground effect during landing or taking off. Simulation results are presented to validate the effectiveness of the proposed controller.
Based on the multiple surface and fixed undirected communication topology, the adaptive leader follower control for multiple quadrotors is discussed. Our approach is based on leader follower architecture. Multiple surface control (MSC) is used to design consensus controller to make multiple quadrotors construct a formation during flying with the presence of uncertainty item caused by the ground effect during landing or taking off. Simulation results are presented to validate the effectiveness of the proposed controller.
2017, 26(2): 197-205.
doi: 10.15918/j.jbit1004-0579.201726.0208
摘要：
Image classification based on bag-of-words (BOW) has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent. To deal with this problem, this paper proposes to combine two ingredients:(i) Three features with functions of mutual complementation are adopted to describe the images, including pyramid histogram of words (PHOW), pyramid histogram of color (PHOC) and pyramid histogram of orientated gradients (PHOG). (ii) An adaptive feature-weight adjusted image categorization algorithm based on the SVM and the decision level fusion of multiple features are employed. Experiments are carried out on the Caltech 101 database, which confirms the validity of the proposed approach. The experimental results show that the classification accuracy rate of the proposed method is improved by 7%-14% higher than that of the traditional BOW methods. With full utilization of global, local and spatial information, the algorithm is much more complete and flexible to describe the feature information of the image through the multi-feature fusion and the pyramid structure composed by image spatial multi-resolution decomposition. Significant improvements to the classification accuracy are achieved as the result.
Image classification based on bag-of-words (BOW) has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent. To deal with this problem, this paper proposes to combine two ingredients:(i) Three features with functions of mutual complementation are adopted to describe the images, including pyramid histogram of words (PHOW), pyramid histogram of color (PHOC) and pyramid histogram of orientated gradients (PHOG). (ii) An adaptive feature-weight adjusted image categorization algorithm based on the SVM and the decision level fusion of multiple features are employed. Experiments are carried out on the Caltech 101 database, which confirms the validity of the proposed approach. The experimental results show that the classification accuracy rate of the proposed method is improved by 7%-14% higher than that of the traditional BOW methods. With full utilization of global, local and spatial information, the algorithm is much more complete and flexible to describe the feature information of the image through the multi-feature fusion and the pyramid structure composed by image spatial multi-resolution decomposition. Significant improvements to the classification accuracy are achieved as the result.
2017, 26(4): 458-467.
doi: 10.15918/j.jbit1004-0579.201726.0405
摘要：
Due to the controllable and reversible properties of the smart magnetorheological (MR) fluid, a novel multiple radial MR valve was developed. The fluid flow channels of the proposed MR valve were mainly composed of two annular fluid flow channels, four radial fluid flow channels and three centric pipe fluid flow channels. The working principle of the multiple radial MR valve was introduced in detail, and the structure optimization design was carried out using ANSYS software to obtain the optimal structure parameters. Moreover, the optimized MR valve was compared with pre-optimized MR valve in terms of their magnetic flux density of radial fluid resistance gap and performance of pressure drop. The experimental test rig was set up to investigate the performance of pressure drop of the proposed MR valve under different currents applied and different loading cases. The results show that the pressure drop between the inlet and outlet port could reach 5.77 MPa at the applied current of 0.8 A. Furthermore, the experimental results also indicate that the loading cases had no effect on the performance of pressure drop.
Due to the controllable and reversible properties of the smart magnetorheological (MR) fluid, a novel multiple radial MR valve was developed. The fluid flow channels of the proposed MR valve were mainly composed of two annular fluid flow channels, four radial fluid flow channels and three centric pipe fluid flow channels. The working principle of the multiple radial MR valve was introduced in detail, and the structure optimization design was carried out using ANSYS software to obtain the optimal structure parameters. Moreover, the optimized MR valve was compared with pre-optimized MR valve in terms of their magnetic flux density of radial fluid resistance gap and performance of pressure drop. The experimental test rig was set up to investigate the performance of pressure drop of the proposed MR valve under different currents applied and different loading cases. The results show that the pressure drop between the inlet and outlet port could reach 5.77 MPa at the applied current of 0.8 A. Furthermore, the experimental results also indicate that the loading cases had no effect on the performance of pressure drop.
2018, 27(4): 535-546.
doi: 10.15918/j.jbit1004-0579.17125
摘要：
A compact annular-radial-orifice flow magnetorheological (MR) valve was developed to investigate the effects of radial resistance gap on pressure drop. The fluid flow paths of this proposed MR valve consist of a single annular flow channel, a single radial flow channel and an orifice flow channel through structure design. The finite element modelling and simulation analysis of the MR valve was carried out using ANSYS/Emag software to investigate the changes of the magnetic flux density and yield stress along the fluid flow paths under the four different radial resistance gaps. Moreover, the experimental tests were also conducted to evaluate the pressure drop, showing that the proposed MR valve has significantly improved its pressure drop at 0.5 mm width of the radial resistance gap when the annular resistance gap is fixed at 1 mm.
A compact annular-radial-orifice flow magnetorheological (MR) valve was developed to investigate the effects of radial resistance gap on pressure drop. The fluid flow paths of this proposed MR valve consist of a single annular flow channel, a single radial flow channel and an orifice flow channel through structure design. The finite element modelling and simulation analysis of the MR valve was carried out using ANSYS/Emag software to investigate the changes of the magnetic flux density and yield stress along the fluid flow paths under the four different radial resistance gaps. Moreover, the experimental tests were also conducted to evaluate the pressure drop, showing that the proposed MR valve has significantly improved its pressure drop at 0.5 mm width of the radial resistance gap when the annular resistance gap is fixed at 1 mm.
2013, 22(2): 171-178.
Abstract:
2013, 22(1): 6-11.
Abstract:
2013, 22(2): 185-190.
Abstract:
2013, 22(1): 1-5.
Abstract:
News & Announcement
Submission & Review
Vol.29,No.4,(December,2020)
ISSN1004-0579
CN11-2916/T
Indexed by EI;Scopus
Eidtor-in-chief:Ran Tao,Beijing Institute of Technology,Beijing,China
