Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots' ability of walking on rough terrain is of great importance but is seldo...
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Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots' ability of walking on rough terrain is of great importance but is seldom achieved. Being compliant to external unperceived impacts is cru- cial since it is unavoidable that the slip, modeling errors and imprecise information of terrain will make planned trajectories to be followed with errors and unpredictable contacts. The impedance control gives an inspiration to realize an active compliance which allows the legged robots to follow reference trajectories and overcome external disturbances. In this paper, a novel impedance force/ position control scheme is presented, which is based on Cartesian force measurement of leg' s end effector for our hydraulic quadruped robot The simulation verifies the efficiency of the impedance model, and the experimental results at the end demonstrate the feasibility of the proposed control scheme.
作者:
Yuanqing XiaSchool of Automation
Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology
The concept of cloud control systems is discussed in this paper, which is an extension of networked control systems (NCSs). With the development of internet of things (IOT), the technology of NCSs has played a key rol...
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The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsio...
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This paper addresses the stochastic stability problem of a modified extended Kalman filter(MEKF), targeted at the state estimation of the nonlinear system through wireless channel, where both transmission failure and ...
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ISBN:
(纸本)9781509009107
This paper addresses the stochastic stability problem of a modified extended Kalman filter(MEKF), targeted at the state estimation of the nonlinear system through wireless channel, where both transmission failure and channel fading are practically under consideration. For a class of nonlinear systems whose observation's Jacobi Matrix is always invertible, the sufficient conditions of the error covariance matrices are accordingly established. Moreover, the conditions for the stochastic stability of the estimation error are also derived, which is tighter than the conditions of boundedness of the error ***, a numerical example is given to demonstrate the feasibility of the proposed method.
This paper proposes an H polytopic lter design for a nonlinear system. Based on the polytopic approximation of the nonlinear system, the polytopic lter design is converted into a group of linear matrix inequalities(L...
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This paper proposes an H polytopic lter design for a nonlinear system. Based on the polytopic approximation of the nonlinear system, the polytopic lter design is converted into a group of linear matrix inequalities(LMIs) so that the polytopic lter parameters can be effectively acquired by numerical convex optimization algorithms. At this stage, the tensor product(TP) model transformation is utilized to compute the polytopic approximation of the nonlinear system. Particularly, a new recti cation procedure is further developed to obtain a specific polytopic approximation with all the vertex systems being stable, which premises the solvability of the LMIs. The method is much easier to be implemented than traditional approaches such as the Hamilton-Jacobi inequality(HJI)-based methods. Simulation demonstrates the method is much less conservative than the existing method and has good estimation performance.
This paper addresses the tuning problem of a proportional-integral-derivative(PID) controller with notch filter for flexible space structure model based on the particle swarm optimization (PSO). For flexible structure...
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Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent p...
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Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could ab- stract the computer user' s operations to a fuzzy cognitive map, and infer the user' s operating inten- tions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.
This paper introduces an attitude updating method based on a new structure of gyroscope-free inertial navigation system(GFINS), in which the angular accelerometers are used to take the place of gyroscopes. For this ne...
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ISBN:
(纸本)9781509041039
This paper introduces an attitude updating method based on a new structure of gyroscope-free inertial navigation system(GFINS), in which the angular accelerometers are used to take the place of gyroscopes. For this new structure of GFINS, a new mathematical model is developed to determine the general three-dimensional motion of body segments. The mathematical model is mainly based on the direction cosine matrix. A second-order differential equation which is represented by angular acceleration should be calculated to solve this problem using the fourth order Runge-Kutta method combining with the interpolation method. Furthermore, the final result of this approach is shown by applying the mathematical model to some simulation data generated by the trajectory generator. The simulation results indicate that the mathematical model has a good performance.
Scale space generation is a fundamental problem in almost all feature extraction algorithms. Often, it is a critical prior step of most image/video analytic applications that are based on the invariance or co-invarian...
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ISBN:
(纸本)9781467374439
Scale space generation is a fundamental problem in almost all feature extraction algorithms. Often, it is a critical prior step of most image/video analytic applications that are based on the invariance or co-invariance of local features, such as SIFT based recognition, matching, and tracking applications. However, it is still quite a challenging problem to enable real-time applications of the extraction of local features due to the fact that scale space generation has a rather large computational complexity. This paper proposes the optimal FPGA design for acceleration of scale space generation. First, in order to derive the mathematical model for scale space generation that fits best in with the FPGA, we have discarded the conventional template convolution based Gaussian filtering scheme and adopted a novel IIR filter based recursive Gaussian blurring algorithm. Then, an approach based on the Retiming technique, which could find the minimal operational period for any given IIR filter, is used to finalize the overall design. For 1024×768 video, the proposed design is able to generate scale spaces at almost 400 fps, which is fast enough to support most real-time applications like object recognition, object matching, and 3D reconstruction.
The integrated navigation system can improve the navigation accuracy utilizing the redundant *** Extended Kalman Filter(EKF) is commonly used in the integrated navigation *** usually takes only one-order of Taylor exp...
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ISBN:
(纸本)9781467383196
The integrated navigation system can improve the navigation accuracy utilizing the redundant *** Extended Kalman Filter(EKF) is commonly used in the integrated navigation *** usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix,which will affect the accuracy and numerical stability of the system *** in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation *** simulation results show that the position,velocity and attitude errors are reduced effectively compared with the EKF *** SCKF method is more suitable for the state estimation problems in integrated navigation system.
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