ORCID Profile
0000-0002-4448-3310
Current Organisation
The Hong Kong Polytechnic University
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: SAGE Publications
Date: 20-03-2020
Abstract: This paper investigates the formation control for noise-tolerance consensus of multi-robotic networks and the mean square consensus condition. Firstly, the multi-robot model is expressed by applying a coordinate transformation based on the Euler-Lagrange equation. Compared with recent works, the control scheme presented in this work can indirectly obtain the evolution trend of position and velocity information of the robot. Besides, the noise and communication delay are involved in the formation control protocol. Secondly, the sufficient conditions of mean square consensus for formation control in multi-robotic networks with communication delay under noisy environments are obtained by using linear matrix inequality schemes. Finally, the numerical simulations are presented and submitted to demonstrate the correctness of the obtained results.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: SAGE Publications
Date: 21-08-2019
Abstract: Based on normal vector and particle swarm optimization (NVP), a point cloud registration algorithm is proposed by searching the corresponding points. It provides a new method for point cloud registration using feature point registration. First, in order to find the nearest eight neighbor nodes, the k-d tree is employed to build the relationship between points. Then, the normal vector and the distance between the point and the center gravity of eight neighbor points can be calculated. Second, the particle swarm optimization is used to search the corresponding points. There are two conditions to terminate the search in particle swarm optimization: one is that the normal vector of node in the original point cloud is the most similar to that in the target point cloud, and the other is that the distance between the point and the center gravity of eight neighbor points of node is the most similar to that in the target point cloud. Third, after obtaining the corresponding points, they are tested by random s le consensus in order to obtain the right corresponding points. Fourth, the right corresponding points are registered by the quaternion method. The experiments demonstrate that this algorithm is effective. Even in the case of point cloud data lost, it also has high registration accuracy.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: SAGE Publications
Date: 28-09-2020
Abstract: This article considers finite-time bounded controller design for one-sided Lipschitz nonlinear differential inclusions. Sufficient conditions of finite-time bounded criterion are given employing convex hull Lyapunov function approach. An algorithm is designed to calculate the finite-time bounded controller. Moreover, a system initial state selection method is presented to find the domain of system initial state aid for transforming quasi-linear matrix inequality–based conditions to linear matrix inequality-based conditions. Finally, a numerical ex le and a comparison experiment ex le are given to illustrate the effectiveness of this proposed design method.
No related grants have been discovered for Yangmin Li.