All Outputs (124)

A robot learning method with physiological interface for teleoperation systems (2019)
Journal Article

The human operator largely relies on the perception of remote environmental conditions to make timely and correct decisions in a prescribed task when the robot is teleoperated in a remote place. However, due to the unknown and dynamic working environ... Read More about A robot learning method with physiological interface for teleoperation systems.

Composite learning adaptive backstepping control using neural networks with compact supports (2019)
Journal Article

© 2019 John Wiley & Sons, Ltd. The ability to learn is crucial for neural network (NN) control as it is able to enhance the overall stability and robustness of control systems. In this study, a composite learning control strategy is proposed for a... Read More about Composite learning adaptive backstepping control using neural networks with compact supports.

Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results (2019)
Journal Article

In this paper, an adaptive trajectory tracking control algorithm for underactuated unmanned surface vessels (USVs) with guaranteed transient performance is proposed. To meet the realistic dynamical model of USVs, we consider that the mass and dam... Read More about Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results.

Force Sensorless Admittance Control with Neural Learning for Robots with Actuator Saturation (2019)
Journal Article

© 1982-2012 IEEE. In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment is defined as linear models with unknow... Read More about Force Sensorless Admittance Control with Neural Learning for Robots with Actuator Saturation.

Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback (2019)
Journal Article

In this paper, an adaptive neural bounded control scheme is proposed for an n-link rigid robotic manipulator with unknown dynamics. With the combination of the neural approximation and backstepping technique, an adaptive neural network control policy... Read More about Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback.

A task learning mechanism for the telerobots (2019)
Journal Article

Telerobotic systems have attracted growing attention because of their superiority in the dangerous or unknown interaction tasks. It is very challengeable to exploit such systems to implement complex tasks in an autonomous way. In this paper, we propo... Read More about A task learning mechanism for the telerobots.

Efficient 3D object recognition via geometric information preservation (2019)
Journal Article

© 2019 Elsevier Ltd Accurate 3D object recognition and 6-DOF pose estimation have been pervasively applied to a variety of applications, such as unmanned warehouse, cooperative robots, and manufacturing industry. How to extract a robust and represent... Read More about Efficient 3D object recognition via geometric information preservation.

Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning (2019)
Journal Article

In this paper, we investigate fuzzy neural network (FNN) control using impedance learning for coordinated multiple constrained robots carrying a common object in the presence of the unknown robotic dynamics and the unknown environment with which the... Read More about Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning.

Admittance-based adaptive cooperative control for multiple manipulators with output constraints (2019)
Journal Article

This paper proposes a novel adaptive control methodology based on the admittance model for multiple manipulators transporting a rigid object cooperatively along a predefined desired trajectory. First, an admittance model is creatively applied to gene... Read More about Admittance-based adaptive cooperative control for multiple manipulators with output constraints.

Adaptive fuzzy Gaussian mixture models for shape approximation in Robot Grasping (2019)
Journal Article

Robotic grasping has always been a challenging task for both service and industrial robots. The ability of grasp planning for novel objects is necessary for a robot to autonomously perform grasps under unknown environments. In this work, we consider... Read More about Adaptive fuzzy Gaussian mixture models for shape approximation in Robot Grasping.

Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery (2019)
Journal Article

© 2016 IEEE. An improved human-robot collaborative control scheme is proposed in a teleoperated minimally invasive surgery scenario, based on a hierarchical operational space formulation of a seven-degree-of-freedom redundant robot. Redundancy is exp... Read More about Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery.

An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions (2019)
Journal Article

Conventional Neural Network (NN) control for robots uses radial basis function (RBF) and for n-link robot with online control, the number of nodes and weighting matrix increases exponentially, which requires a number of calculations to be performed w... Read More about An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions.

Enhanced teleoperation performance using hybrid control and virtual fixture (2019)
Journal Article

To develop secure, natural and effective teleoperation, the perception of the slave plays a key role for the interaction of a human operator with the environment. By sensing slave information, the human operator can choose the correct operation in a... Read More about Enhanced teleoperation performance using hybrid control and virtual fixture.

Encoding Multiple Sensor Data for Robotic Learning Skills from Multimodal Demonstration (2019)
Journal Article

© 2013 IEEE. Learning a task such as pushing something, where the constraints of both position and force have to be satisfied, is usually difficult for a collaborative robot. In this work, we propose a multimodal teaching-by-demonstration system whic... Read More about Encoding Multiple Sensor Data for Robotic Learning Skills from Multimodal Demonstration.

A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System (2019)
Journal Article

© 2013 IEEE. Performance of teleoperation can be greatly influenced by time delay in the process of tele-manipulation with respect to accuracy and transparency. Wave variable is an effective algorithm to achieve a good stable capability. However, som... Read More about A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System.

Estimation of EMG-Based force using a neural-network-based approach (2019)
Journal Article

© 2013 IEEE. The dynamics of human arms has a high impact on the humans' activities in daily life, especially when a human operates a tool such as interactions with a robot with the need for high dexterity. The dexterity of human arms depends largely... Read More about Estimation of EMG-Based force using a neural-network-based approach.

Head-raising of snake robots based on a predefined spiral curve method (2018)
Journal Article

© 2018 by the authors. A snake robot has to raise its head to acquire a wide visual space for planning complex tasks such as inspecting unknown environments, tracking a flying object and acting as a manipulator with its raising part. However, only a... Read More about Head-raising of snake robots based on a predefined spiral curve method.

A neural-network-based controller for piezoelectric-actuated stick-slip devices (2017)
Journal Article

© 1982-2012 IEEE. Piezoelectric-actuated stick-slip device (PASSD) is a highly promising equipment that is composed of one end-effector, one piezoelectric actuator (PEA) and one driving object adhered to the PEA. Since the end-effector can slip on th... Read More about A neural-network-based controller for piezoelectric-actuated stick-slip devices.

Extended state observer-based integral sliding mode control for an underwater robot with unknown disturbances and uncertain nonlinearities (2017)
Journal Article

© 2017 IEEE. This paper develops a novel integral sliding mode controller (ISMC) for a general type of underwater robots based on multiple-input and multiple-output extended-state-observer (MIMO-ESO). The difficulties associated with the unmeasured v... Read More about Extended state observer-based integral sliding mode control for an underwater robot with unknown disturbances and uncertain nonlinearities.

Development of a dynamics model for the Baxter robot (2016)
Presentation / Conference Contribution

© 2016 IEEE. The dynamics model of a robot is important to find the relation between the joint actuator torques and the resulting motion. There are two common methods to do this: The Lagrange formulation, which gives a closed form of the dynamics equ... Read More about Development of a dynamics model for the Baxter robot.