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Biomechanics And Motor Control Of Human Movement

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L2 Gain And Passivity Techniques In Nonlinear Control

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.

A Survey on Artificial Intelligence Trends in Spacecraft Guidance Dynamics and Control

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.

Textile Technology for Soft Robotic and Autonomous Garments

An adaptive sliding mode controller was designed for a mobile robot driven by four mecanum wheels.The original contribution of this paper is employing adaptive robust controller to mecanum wheels driven mobile robot for obtaining better tracking and robustness performance.To complete the design of the controller, the kinematic model of the mobile robot driven by mecanum wheels was firstly proposed.An adaptive robust controller was designed subsequently.A sliding surface was designed in Proportional-Differential-Integral form, which satisfied the robustness requirements of the system.Besides, a reaching law which has quick convergence was introduced, which reduced the time consumed by the setting parameters and resisting external disturbance.The controller was demonstrated in the presence of impulsive disturbance and sinusoidal signal disturbance, which proved the superiority of the proposed controller.Finally, an experimental verification of trajectory tracking was implemented to verify the practicability and effectiveness.

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An Adaptive Robust Controller for a Mobile Robot Driven by Mecanum Wheels

The absolute attitude error of chaser vehicle is always neglected in observation equation of space relative navigation filter when chaser satellite on-board radar using as the measurement sensor. But the attitude error could affect relative navigation filter precision in fact. The new observation equation, which contains the absolute attitude error of chaser vehicle, is constructed. And the plan, using equivalent measurement error as attitude error, is put forward. The simulations show that the filter precision of relative position and velocity descend when attitude error is big, and the precision is improved when attitude equivalent error is introduced to filter. The plan of attitude equivalent error is proved to be feasible.

Space Relative Navigation Filter Based On-Board Radar Observation

Optimal configuration for dual-arm space robot grasping a tumbling target based on task compatibility

Wearable robotics is a potential solution in aiding gait rehabilitation of lower limbs dyskinesia patients, such as knee osteoarthritis or stroke afflicted patients. Many wearable robots have been developed in the form of rigid exoskeletons, but their bulk devices, high cost and control complexity hinder their popularity in the field of gait rehabilitation. Thus, the development of a portable, compliant and low-cost wearable robot for gait rehabilitation is necessary. Inspired by Chinese traditional folding fans and balloon inflators, the authors present an inflatable, foldable and variable stiffness knee exosuit (IFVSKE) in this paper. The pneumatic actuator of IFVSKE was fabricated in the shape of folding fans by using thermoplastic polyurethane (TPU) fabric materials. The geometric and mechanical properties of IFVSKE were characterized with experimental methods. To assist the knee joint smartly, an intelligent control profile for IFVSKE was proposed based on the concept of full-cycle energy management of the biomechanical energy during human movement. The biomechanical energy of knee joints in a walking gait cycle of patients could be collected and released to assist the joint motion just by adjusting the inner pressure of IFVSKE. Finally, a healthy subject was involved to walk with and without the IFVSKE to evaluate the assisting effects. Keywords—Biomechanical energy management, gait rehabilitation, knee exosuit, wearable robotics.

/pdf/an-inflatable-and-foldable-knee-exosuit-based-on-intelligent-3djen1ybwg.pdf

An Inflatable and Foldable Knee Exosuit Based on Intelligent Management of Biomechanical Energy

For trajectory planning problem with multiconstraints of free-floating space robots (FFSR), the optimal solution may be unavailable due to strict constraints. In order to avoid identify a solution and obtain an executable joint trajectory, this paper proposes a trajectory planning method based on dual-mode switching. Using this method, the planner can automatically switch between the optimal mode and the effective mode, and obtain a feasible joint trajectory that satisfies the task requirements when the end-effector tracking error constraint and the joint torque constraint are considered. In this paper, the multiconstraints model of FFSR, which mainly consider control and dynamic constraints and the trajectory planning model based on dual-mode switching, are established, and the corresponding solving method is presented. The simulation results demonstrate that the proposed method is effective and feasible. 

Mingming Wang

Papers

An Adaptive Robust Controller for a Mobile Robot Driven by Mecanum Wheels

Space Relative Navigation Filter Based On-Board Radar Observation

Optimal configuration for dual-arm space robot grasping a tumbling target based on task compatibility

An Inflatable and Foldable Knee Exosuit Based on Intelligent Management of Biomechanical Energy

Trajectory Planning of Free-Floating Space Robot Based on Dual-Mode Switching