Gait phase detection is of great significance in the field of motion analysis and exoskeleton-assisted walking, and can realize the accurate control of exoskeleton robots. Therefore, in order to obtain accurate gait information and ensure good gait phase detection accuracy, a gait recognition framework based on the New Hidden Markov Model (NHMM) is proposed to improve the accuracy of gait phase detection. A multi-sensor gait data acquisition system was developed and used to collect the training data of eight healthy subjects to measure the acceleration and plantar pressure of the human body. Accuracy of the recognition framework, filtering algorithm and window selection, and the missing validation of the generalization performance of the method were evaluated. The experimental results show that the overall accuracy of NHMM is 94.7%, which is better than all other algorithms. The generalization of the performance is 84.3%. The results of this study provide a theoretical basis for the design and control of the exoskeleton.

According to the characteristics of human gait and the requirements of power assistance, locomotive mechanisms and electrohydraulic servo driving are designed on a lower limb exoskeleton robot, in which the miniaturization and lightweight of driving system are realized. The kinematics of the robot is analyzed and verified via the typical movements of the exoskeleton. In this article, the simulation on the power of joints during level walking was analyzed in ADAMS 2016, which is a multibody simulation and motion analysis software. Motion ranges and driving strokes are then optimized. A proportional integral derivative (PID) control method with error estimation and pressure compensation is proposed to satisfy the requirements of joints power assistance and comply with the motion of human lower limb. The proposed method is implemented into the exoskeleton for assisted walking and is verified by experimental results. Finally, experiments show that the tracking accuracy and power-assisted performance of exoskeleton robot joints are improved.

With the continuous expansion of the application field of mobile robots, the diversification and complexity of the application scenarios have put forward higher requirements for their motion control performance. In order to enhance the ability to brake fast and to prevent slipping when the mobile robot is working, a slipping ratio tracking strategy based on an improved integral sliding mode algorithm regulated by a composite convergence law is proposed. The composite convergence law is proposed by integrating the power law with the exponential convergence law. A mathematical model of a single-wheeled mobile robot is established, a relationship curve between slipping ratio and pavement adhesion coefficient is introduced to estimate the pavement adhesion coefficient, and an improved integral sliding mode controller is designed. The stability is verified using Lyapunov stability theory. The slipping ratio is tracked based on the integral sliding-mode controller, and the slipping ratio is corrected to control the wheel slipping ratio near the ideal optimal slipping ratio. Furthermore, simulation experiments are conducted in MATLAB/Simulink (R2020b) under two typical working conditions to compare the proposed control strategy with conventional sliding-mode control regulated by an exponential convergence law. Finally, the mobile robot slipping ratio tracking experiments are conducted to verify the simulation results, which show that the proposed control strategy enables the mobile robot to reach the ideal braking state more quickly and stably, thereby improving the braking effect of the ABS braking system of the mobile robots.

Research on space docking technology was first motivated by the application scenario of space station docking in the aviation field. Due to the maturity of this technology, its application field is expanding to other industries. To benefit the intelligent transportation field, this study uses space docking technology to realize combination and reconstruction between car bodies. Different spatial docking methods and structural characteristics are determined by different application scenarios. The docking of the space station is completed in the suspended state of the body in the outer space environment, which requires advanced technology, is high in hardware cost, and involves a small channel diameter. In this study, the docking of the reconstructed vehicle is completed on the ground; thus, it is low in hardware cost and involves a large channel diameter. Based on the above technical requirements, a three−point circular peripheral docking method is designed for the reconstructed vehicle. A visual positioning system is built, the mapping relationship between the camera coordinate system and the landmark coordinate system rotation matrix and translation vector is established, and the adaptive capture behavior is realized by path planning through the inverse pose solution model. Simulation experiments demonstrate that the active and passive vehicle bodies can achieve compliance capture with small collision force under the two conditions of forward collision and oblique collision, and the recovery coefficient after collision and docking is in the range of (0, 0.01). The acceleration decay process under two working conditions is measured in the crash test of a sample vehicle, which verifies the feasibility of the space reconstruction of the vehicle docking mechanism and the ability of this configuration to achieve tasks, providing a constructive idea for space docking technology with a large channel diameter.