Fusheng Zha

CPG Control for Biped Hopping Robot in Unpredictable Environment

A CPG control mechanism is proposed for hopping motion control of biped robot in unpredictable environment. Based on analysis of robot motion and biological observation of animal’s control mechanism, the motion control task is divided into two simple parts: motion sequence control and output force control. Inspired by a two-level CPG model, a two-level CPG control mechanism is constructed to coordinate the drivers of robot joint, while various feedback information are introduced into the control mechanism. Interneurons within the control mechanism are modeled to generate motion rhythm and pattern promptly for motion sequence control; motoneurons are modeled to control output forces of joint drivers in real time according to feedbacks. The control system can perceive changes caused by unknown perturbations and environment changes according to feedback information, and adapt to unpredictable environment by adjusting outputs of neurons. The control mechanism is applied to a biped hopping robot in unpredictable environment on simulation platform, and stable adaptive motions are obtained.

Passive Acoustic Source Localization at a Low Sampling Rate Based on a Five-Element Cross Microphone Array

Accurate acoustic source localization at a low sampling rate (less than 10 kHz) is still a challenging problem for small portable systems, especially for a multitasking micro-embedded system. A modification of the generalized cross-correlation (GCC) method with the up-sampling (US) theory is proposed and defined as the US-GCC method, which can improve the accuracy of the time delay of arrival (TDOA) and source location at a low sampling rate. In this work, through the US operation, an input signal with a certain sampling rate can be converted into another signal with a higher frequency. Furthermore, the optimal interpolation factor for the US operation is derived according to localization computation time and the standard deviation (SD) of target location estimations. On the one hand, simulation results show that absolute errors of the source locations based on the US-GCC method with an interpolation factor of 15 are approximately from 1/15- to 1/12-times those based on the GCC method, when the initial same sampling rates of both methods are 8 kHz. On the other hand, a simple and small portable passive acoustic source localization platform composed of a five-element cross microphone array has been designed and set up in this paper. The experiments on the established platform, which accurately locates a three-dimensional (3D) near-field target at a low sampling rate demonstrate that the proposed method is workable.

A parallel actuated pantograph leg for high-speed locomotion

High-speed running is one of the most important topics in the field of legged robots which requires strict constraints on structural design and control. To solve the problems of high acceleration, high energy consumption, high pace frequency and ground impact during high-speed movement, this paper presents a parallel actuated pantograph leg with an approximately decoupled configuration. The articulated leg features in light weight, high load capacity, high mechanical efficiency and structural stability. The similarity features of force and position between the control point and the foot are analyzed. The key design parameters, K1 and K2, which concern the dynamic performances, are carefully optimized by comprehensive evaluation of the leg inertia and mass within the maximum foot trajectory. A control strategy that incorporates virtual Spring Loaded Inverted Pendulum (SLIP) model and active force is also proposed to test the design. The strategy can implement highly flexible impedance without mechanical springs, which substantially simplifies the design and satisfies the variable stiffness requirements during high-speed running. The rationality of the structure and the effectiveness of the control law are validated by simulation and experiments.

Stability analysis of quasi-periodic hopping of a passive one-legged robot with compliant hip joint

Aimed at improving energy efficiency of legged robots, flexible elements like springs are introduced to realize temporary energy storage. To achieve the excellent locomotion performance of animals, it is necessary to introduce the torsional spring at the revolute joint into the robot. This paper focuses on a simplified one-legged robot with compliant hip joint, and studies the influence of the torsional spring on the stability of robot quasi-periodic hopping. Firstly, the dynamics differential equations of stance phase and flight phase are established and solved by numerical and analytical methods respectively. Then Poincare map of one whole hopping cycle is built through the unity of four sub-maps. In condition of completely passive hopping of the robot, fixed points are searched through cell mapping and orthogonal table methods. Finally, quasi-periodic solution is obtained, and its stability is analyzed. The analysis results show that the introduced flexible element in revolute joint deteriorates the stability of robot hopping.

Real-Time Filtering Method Based on Neuron Filtering Mechanism and Its Application on Robot Speed Signals

In order to implement the real-time filtering and tracking of robot signals with high efficiency, a novel real-time filtering method based on neuron filtering mechanism is developed in this paper. By considering the ubiquity of resonance in mammal and combining the mechanism of neural information processing, the derived details and the feasible parameter criterion under minimum error variance condition are given. For illustration, the application on quadruped robot is discussed. The quadruped robot feet speed signals are processed by developed real-time filtering method and Kalman filtering algorithm, respectively, and the computation time of both methods is tested. Experiment results show that the performance of developed real-time filtering method is better than that of Kalman filtering algorithm, not only in filtering and tracking performance but also in filtering speed. The novel real-time filtering method based on neuron filtering mechanism can effectively implement the real-time filtering and tracking with regard to robot signals.

Potassium ion channel optical model: Membrane potential repolarization and its dynamic spread process

This paper presents single and multi-potassium ion channel optical models based on optical point spread function and linear superposition principle. Its novelty lies in the dynamic description method of potential diffusion process which is generated by the whole membrane and nearby ion channel while potassium ion channels open. The main parameters and the corresponding equations of proposed model are studied. The dynamic spatiotemporal spread processes of membrane potential repolarization evoked by opened potassium ion channels are investigated as well. Furthermore, performance evaluation by computer simulation and experimental results proves the correctness and effectiveness of the idea above.

Sodium ion channel optical model: Depolarization spatial distribution and local potential dynamic spatiotemporal processes

This paper is concerned with the development of a novel sodium ion channel optical model by using the equivalent lens point spread function and the optical linear superposition principle. The main parameters and the corresponding equations of proposed model are studied and calculated. The relationship among the optical response index, membrane potential and time is investigated as well. Furthermore, performance evaluation by simulating and analyzing the membrane depolarization, the local potential and the dynamic spatiotemporal processes are undertaken to prove the correctness and effectiveness of the proposed model.

Development of a fast filtering algorithm via vibration systems approach and application to a class of portable vital signs monitoring systems

This paper is concerned with the development of a fast filtering algorithm for portable embedded systems based on vibration systems approach. Compared with the existing particle filters and fast wavelet transform filters, the performance of the filter output is remarkably improved by the developed filtering algorithm. The total computation time of the filtering algorithm is both less than that of the particle filter and fast wavelet transform filter. Further, the filtering algorithm is applied to a class of portable vital signs monitoring system, by which the effectiveness of the filtering algorithm is clearly demonstrated.

A neural network growing algorithm based on Brownian movement and gravity constraint

A growing algorithm of neural network based on axon growth is developed in this article. At the beginning, the Newtonian gravitation and the Brownian motion are employed to establish an axon growth model, and the constraint function of the neural axon growth is derived according to the gravitational coefficient and the Brown coefficient. And then, the growing algorithm of neural network is obtained on the basis of the output function of neural network. Simulation experiments show that the developed algorithm can simulate the process that different neurons connect each other by their axon growth to establish neural network. And at the end, the developed algorithm is applied to the rhythmic motion control of a quadruped robot to verify the effectiveness in walk gait and in trot gait, respectively.

A velocity estimation algorithm for legged robot

To secure the data accuracy while reducing development cost of robot, in this article, we conducted fusion estimation of the information measured by strapdown inertial navigation system and the information solved by forward kinematics using extended Kalman filter and regarding the motion parameter error was proposed as state variable. On this basis, state equation and detecting equation can be established. In addition, this article made innovative attempt to compensate the optimal estimation of motion parameter error using feedback correction method, and finally obtained stable and accurate velocity estimation of robot. Being unrestricted by the number of robot’s leg, this method is suitable for both static gait and dynamic gait, and can overcome the impact from leg slipping. As for the verification of this method, in this article, a quadruped robot was employed for motion simulation and experimental verification, and results verified the correctness and feasibility of the proposed method.