scispace - formally typeset
Search or ask a question
Author

Mingming Wang

Bio: Mingming Wang is an academic researcher from Northwestern Polytechnical University. The author has contributed to research in topics: Robot & Trajectory. The author has an hindex of 11, co-authored 44 publications receiving 468 citations. Previous affiliations of Mingming Wang include Technische Universität München.

Papers published on a yearly basis

Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the authors investigated the application of Particle Swarm Optimization (PSO) strategy to trajectory planning of the kinematically redundant space robot in free-floating mode.

105 citations

Journal ArticleDOI
TL;DR: Differ from traditional methods, null-space and specialized curve are synthesized to provide a novel viewpoint for trajectory planning of free-floating space robot and a constrained differential evolution scheme with premature handling strategy is implemented to find the optimal solution of the design variables.

82 citations

Journal ArticleDOI
TL;DR: The issue of the space robot motion control is reformulated by using NMPC with predefined objectives under input, output and obstacle constraints over a receding horizon by using an on-line quadratic programming procedure to obtain the constrained optimal control decisions in real-time.

73 citations

Journal ArticleDOI
TL;DR: This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode and shows the effectiveness of the proposed method.

72 citations

Journal ArticleDOI
TL;DR: Simulation results are presented for detumbling a target with rotational motion using a seven degree-of-freedom redundant space manipulator, which demonstrates the feasibility and effectiveness of the proposed method.
Abstract: This paper focuses on the motion planning to detumble and control of a space robot to capture a non-cooperative target satellite. The objective is to construct a detumbling strategy for the target and a coordination control scheme for the space robotic system in post-capture phase. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling strategy for the post-capture phase is proposed based on the quartic B $$\acute{\text{ e }}$$ zier curves and adaptive particle swarm optimization algorithm subject to the specific constraints. Both detumbling time and control torques were taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is designed to track the designed reference path while regulating the attitude of the chaser to a desired value. The space robot successfully dumps the initial velocity of the tumbling satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a seven degree-of-freedom redundant space manipulator, which demonstrates the feasibility and effectiveness of the proposed method.

51 citations


Cited by
More filters
01 Jan 2016
TL;DR: Biomechanics and motor control of human movement is downloaded so that people can enjoy a good book with a cup of tea in the afternoon instead of juggling with some malicious virus inside their laptop.
Abstract: Thank you very much for downloading biomechanics and motor control of human movement. Maybe you have knowledge that, people have search hundreds times for their favorite books like this biomechanics and motor control of human movement, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their laptop.

1,689 citations

01 Jan 2016
TL;DR: L2 gain and passivity techniques in nonlinear control is downloaded for free to help people who are facing with some harmful virus inside their desktop computer.
Abstract: Thank you very much for downloading l2 gain and passivity techniques in nonlinear control. Maybe you have knowledge that, people have search numerous times for their chosen books like this l2 gain and passivity techniques in nonlinear control, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some harmful virus inside their desktop computer.

655 citations

Journal ArticleDOI
01 Dec 2019
TL;DR: In this paper, the authors focus on evolutionary optimisation, tree searches and machine learning, including deep learning and reinforcement learning, as the key technologies and drivers for current and future research in the field of spacecraft guidance dynamics and control.
Abstract: The rapid developments of artificial intelligence in the last decade are influencing aerospace engineering to a great extent and research in this context is proliferating. We share our observations on the recent developments in the area of spacecraft guidance dynamics and control, giving selected examples on success stories that have been motivated by mission designs. Our focus is on evolutionary optimisation, tree searches and machine learning, including deep learning and reinforcement learning as the key technologies and drivers for current and future research in the field. From a high-level perspective, we survey various scenarios for which these approaches have been successfully applied or are under strong scientific investigation. Whenever possible, we highlight the relations and synergies that can be obtained by combining different techniques and projects towards future domains for which newly emerging artificial intelligence techniques are expected to become game changers.

125 citations

Posted Content
TL;DR: A focus is on evolutionary optimisation, tree searches and machine learning, including deep learning and reinforcement learning as the key technologies and drivers for current and future research in the field.
Abstract: The rapid developments of Artificial Intelligence in the last decade are influencing Aerospace Engineering to a great extent and research in this context is proliferating. We share our observations on the recent developments in the area of Spacecraft Guidance Dynamics and Control, giving selected examples on success stories that have been motivated by mission designs. Our focus is on evolutionary optimisation, tree searches and machine learning, including deep learning and reinforcement learning as the key technologies and drivers for current and future research in the field. From a high-level perspective, we survey various scenarios for which these approaches have been successfully applied or are under strong scientific investigation. Whenever possible, we highlight the relations and synergies that can be obtained by combining different techniques and projects towards future domains for which newly emerging artificial intelligence techniques are expected to become game changers.

125 citations