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Adaptive dynamic programming-based controller with admittance adaptation for robot–environment interaction (2020)
Journal Article

The problem of optimal tracking control for robot–environment interaction is studied in this article. The environment is regarded as a linear system and an admittance control with iterative linear quadratic regulator method is obtained to guarantee t... Read More about Adaptive dynamic programming-based controller with admittance adaptation for robot–environment interaction.

Disturbance observer-based fault-tolerant control for robotic systems with guaranteed prescribed performance (2020)
Journal Article

The actuator failure compensation control problem of robotic systems possessing dynamic uncertainties has been investigated in this paper. Control design against partial loss of effectiveness (PLOE) and total loss of effectiveness (TLOE) of the actua... Read More about Disturbance observer-based fault-tolerant control for robotic systems with guaranteed prescribed performance.

Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models (2020)
Journal Article

© 2020, The Author(s). Hand gesture is one of the most intuitive and natural ways for human to communicate with computers, and it has been widely adopted in many human–computer interaction applications. However, it is still a challenging problem when... Read More about Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models.

Information entropy-based intention prediction of aerial targets under uncertain and incomplete information (2020)
Journal Article

© 2020 by authors. To improve the effectiveness of air combat decision-making systems, target intention has been extensively studied. In general, aerial target intention is composed of attack, surveillance, penetration, feint, defense, reconnaissance... Read More about Information entropy-based intention prediction of aerial targets under uncertain and incomplete information.

A sEMG-based shared control system with no-target obstacle avoidance for omnidirectional mobile robots (2020)
Journal Article

We propose a novel shared control strategy for mobile robots in a human-robot interaction manner based on surface eletromyography (sEMG) signals. For security reasons, an obstacle avoidance scheme is introduced to the shared control system as collisi... Read More about A sEMG-based shared control system with no-target obstacle avoidance for omnidirectional mobile robots.

Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators (2019)
Journal Article

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human-robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge tec... Read More about Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators.

A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller (2019)
Journal Article

© 2019 Elsevier B.V. Robot learning from demonstration (LfD) enables robots to be fast programmed. This paper presents a novel LfD framework involving a teaching phase, a learning phase and a reproduction phase, and proposes methods in each of these... Read More about A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller.

A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone (2019)
Journal Article

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. As a significant role in healthcare and sports applications, human activity recognition (HAR) techniques are capable of monitoring humans’ daily behavior. It has spurred the demand for intelli... Read More about A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone.