Classical PID controllers usually rely on some prior knowledge to manually adjust the gains of the controller and determine them. However, when the mobile robot works in a complex and changeable environment, the fixed PID gains may be difficult to meet the needs of the robot trajectory tracking accuracy. Therefore, this paper proposes a Q-learning-based adaptive PID trajectory tracking algorithm. Firstly, we construct a trajectory tracking Q-PID controller based on the error model of mobile robot. Then, the Q-learning algorithm is used to adaptively adjust the gains of the PID controller online. Meanwhile, the incremental active learning exploration method is used to improve learning efficiency and adaptability of agent. Finally, we use simulation experiments to verify the high performance of our algorithm.
A kind of ZMP measure system has been described in this paper, tests have been done on person with the system.The obtained experimental ZMP trajectory has been analyzed and real-time performance of this system has also been verified.So, the result has shown that the system can be implemented on our 6 DOF biped robot.The ultimate purpose of this system is to measure ZMP trajectory for further analysis of on-line gait planning of the biped robot.
Introduction Shape memory alloy (SMA) actuators are attractive options for robotic applications due to their salient features. So far, achieving precise control of SMA actuators and applying them to human-robot interaction scenarios remains a challenge. Methods This paper proposes a novel approach to deal with the control problem of a SMA actuator. Departing from conventional mechanism models, we attempt to describe this nonlinear plant using a gray-box model, in which only the input current and the output displacement are measured. The control scheme consists of the model parameters updating and the control law calculation. The adaptation algorithm is founded on the multi-innovation concept and incorporates a dead-zone weighted factor, aiming to concurrently reduce computational complexities and enhance robustness properties. The control law is based on a PI controller, the gains of which are designed by the pole assignment technique. Theoretical analysis proves that the closed-loop performance can be ensured under mild conditions. Results The experiments are first conducted through the Beckhoff controller. The comparative results suggest that the proposed adaptive PI control strategy exhibits broad applicability, particularly under load variations. Subsequently, the SMA actuator is designed and incorporated into the hand rehabilitation robot. System position tracking experiments and passive rehabilitation training experiments for various gestures are then conducted. The experimental outcomes demonstrate that the hand rehabilitation robot, utilizing the SMA actuator, achieves higher position tracking accuracy and a more stable system under the adaptive control strategy proposed in this paper. Simultaneously, it successfully accommodates hand rehabilitation movements for multiple gestures. Discussion The adaptive controller proposed in this paper takes into account both the computational complexity of the model and the accuracy of the control results, Experimental results not only demonstrate the practicality and reliability of the controller but also attest to its potential application in human-machine interaction within the field of neural rehabilitation.
This paper provides the design and implementation of navigation and control software for an aerospace-level lunar rover validation system. Based on analysing structure characteristics of the navigation and control system, real-time navigation and control software involving interrupt service routine, tasks, and task-task communication is designed and implemented within the embedded operation system VxWorks. Although the current research of our project is still on the way, this navigation and control software designed here is already successfully applied in some of physical experiments on the lunar rover platform. The practical employment indicates the utility and reliability of the designed software totally satisfying design requirements of the navigation and control system.
Surface electromyography (sEMG), a human-machine interface for gesture recognition, has shown promising potential for decoding motor intentions, but a variety of nonideal factors restrict its practical application in assistive robots. In this paper, we summarized the current mainstream gesture recognition strategies and proposed a gesture recognition method based on multimodal canonical correlation analysis feature fusion classification (MCAFC) for a nonideal condition that occurs in daily life, i.e., posture variations. The deep features of the sEMG and acceleration signals were first extracted via convolutional neural networks. A canonical correlation analysis was subsequently performed to associate the deep features of the two modalities. The transformed features were utilized as inputs to a linear discriminant analysis classifier to recognize the corresponding gestures. Both offline and real-time experiments were conducted on eight non-disabled subjects. The experimental results indicated that MCAFC achieved an average classification accuracy, average motion completion rate, and average motion completion time of 93.44%, 94.05%, and 1.38 s, respectively, with multiple dynamic postures, indicating significantly better performance than that of comparable methods. The results demonstrate the feasibility and superiority of the proposed multimodal signal feature fusion method for gesture recognition with posture variations, providing a new scheme for myoelectric control.
Aimed at structure of humanoid robot and requirements for control performance, this paper designs and realizes joint controller based on CAN bus, and structures an effective credible control system by connecting all joint controllers, force sensors, task management computer and upper limbs control computer together; and realizes the transmission of audio and video information by wireless LAN; constitutes whole control system of humanoid robot. Characteristics of the system are simple structure, high reliability, good real-time, and friendly human-machine interface. This paper includes mainly: overall structure of the humanoid robot, design and implement of controller, topology of control system, and bring forward some imaginations to enhance performance of the control system
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) as one big-science project in the Ninth Five-Year Plan period (1996-2000) is a meridian reflecting Schmidt telescope. The MA active optics system is the key technique and the difficult point of LAMOST. In this paper, a distributed control system based on CANBUS is presented to be used for controlling the MA,and the framework and working of this distributed control system is discussed.
Reliable mapping and hazard detection are prerequisites for autonomous navigation for unmanned ground vehicles. Because of the uncertainty and vibration induced by high-speed navigation and rugged terrain, the problem of mapping for high-speed off-road autonomous navigation has not been completely solved yet. A relative probabilistic mapping (RPM) algorithm is introduced to address the problem. Firstly, the relative probabilistic map is updated by Kalman filter and Gaussian Mixture algorithm based on the probabilistic exteroceptive measurements model. Then, terrain traversability is evaluated to identify obstacles in the map. Experiments on off-road high-speed autonomous vehicle, which suffers from severe vibration, with different sensor configurations are carried out to demonstrate the capability of the RPM algorithm.
The Arctic and Antarctic, as the harshest environments on the earth, are of great importance to the nation. The extreme environments can be harmful, even fatal, to human beings and mobile robots. To execute missions on the Antarctic in place of human, the State Key Laboratory of Robotics of Shenyang Institute of Automation, Chinese Academy of Sciences has designed three generations of Antarctic rovers. The hardware and software design and implementation of the third generation of Antarctic rover, which has been tested on the Antarctic during the 28th Chinese National Antarctic Research Expedition in 2011, will be presented in this paper. The preliminary experimental results, as introduced in the last part of the paper, suggest that the design and implementation of the hardware and software system can ensure efficiency and reliability of the rover working on the Antarctic.
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