All Outputs (125)

A multimodal teleoperation interface for human-robot collaboration (2023)
Presentation / Conference Contribution

Human-robot collaboration provides an effective approach to combine human intelligence and the autonomy of robots, which can improve the safety and efficiency of the robot. However, developing an intuitive and immersive human-robot interface with mul... Read More about A multimodal teleoperation interface for human-robot collaboration.

The classification and new trends of shared control strategies in telerobotic systems: A survey (2023)
Journal Article

Shared control, which permits a human operator and an autonomous controller to share the control of a telerobotic system, can reduce the operator's workload and/or improve performances during the execution of tasks. Due to the great benefits of combi... Read More about The classification and new trends of shared control strategies in telerobotic systems: A survey.

Adaptive fuzzy prescribed-time connectivity-preserving consensus of stochastic nonstrict-feedback switched multiagent systems (2023)
Journal Article

An adaptive fuzzy prescribed-time connectivity-preserving consensus protocol is designed for a class of stochastic nonstrict-feedback multiagent systems, in which periodic disturbances, switched nonlinearities, input saturation, and limited communica... Read More about Adaptive fuzzy prescribed-time connectivity-preserving consensus of stochastic nonstrict-feedback switched multiagent systems.

Editorial: Neuromorphic engineering for robotics (2023)
Journal Article

Neuromorphic engineering aims to apply insights from neurobiology to develop next-generation artificial intelligence for computation, sensing, and the control of robotic systems. There has been a rapid expansion of neuromorphic engineering technologi... Read More about Editorial: Neuromorphic engineering for robotics.

Editorial: Advanced learning control in physical interaction tasks (2023)
Journal Article

Robotics are increasingly and urgently expected to acquire human-like dexterous manipulation skills in physical interaction environments. Due to this, the loop between the high-level action policy and the low-level motion execution needs to be closed... Read More about Editorial: Advanced learning control in physical interaction tasks.

Review on human-like robot manipulation using dexterous hands (2023)
Journal Article

In recent years, human hand-based robotic hands or dexterous hands have gained attention due to their enormous capabilities of handling soft materials compared to traditional grippers. Back in the earlier days, the development of a hand model close t... Read More about Review on human-like robot manipulation using dexterous hands.

A comprehensive review of scab disease detection on Rosaceae family fruits via UAV imagery (2023)
Journal Article

Disease detection in plants is essential for food security and economic stability. Unmanned aerial vehicle (UAV) imagery and artificial intelligence (AI) are valuable tools for it. The purpose of this review is to gather several methods used by our p... Read More about A comprehensive review of scab disease detection on Rosaceae family fruits via UAV imagery.

A gripper-like exoskeleton design for robot grasping demonstration (2023)
Journal Article

Learning from demonstration (LfD) is a practical method for transferring skill knowledge from a human demonstrator to a robot. Several studies have shown the effectiveness of LfD in robotic grasping tasks to improve the success rate of grasping and t... Read More about A gripper-like exoskeleton design for robot grasping demonstration.

Deformation-aware contact-rich manipulation skills learning and compliant control (2023)
Presentation / Conference Contribution

In this paper, we study a vision-based reactive adaptation method for contact-rich manipulation tasks, based on the compliant control and learning from demonstration. For contact-rich tasks, the compliant control method is essential, especially when... Read More about Deformation-aware contact-rich manipulation skills learning and compliant control.

Human-in-the-loop Learning and Control for Robot Teleoperation (2023)
Book

Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning tech... Read More about Human-in-the-loop Learning and Control for Robot Teleoperation.

Multi-fingered tactile servoing for grasping adjustment under partial observation (2022)
Presentation / Conference Contribution

Grasping of objects using multi-fingered robotic hands often fails due to small uncertainties in the hand motion control and the object's pose estimation. To tackle this problem, we propose a grasping adjustment strategy based on tactile seroving. Ou... Read More about Multi-fingered tactile servoing for grasping adjustment under partial observation.

One-shot domain-adaptive imitation learning via progressive learning applied to robotic pouring (2022)
Journal Article

Traditional deep learning-based visual imitation learning techniques require a large amount of demonstration data for model training, and the pre-trained models are difficult to adapt to new scenarios. To address these limitations, we propose a unifi... Read More about One-shot domain-adaptive imitation learning via progressive learning applied to robotic pouring.

A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control (2022)
Journal Article

Due to changes in the environment and errors that occurred during skill initialization, the robot's operational skills should be modified to adapt to new tasks. As such, skills learned by the methods with fixed features, such as the classical Dynamic... Read More about A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control.

A neural network based framework for variable impedance skills learning from demonstrations (2022)
Journal Article

Robots are becoming standard collaborators not only in factories, hospitals, and offices, but also in people's homes, where they can play an important role in situations where a human cannot complete a task alone or needs the help of another person (... Read More about A neural network based framework for variable impedance skills learning from demonstrations.

A modified LSTM model for Chinese sign language recognition using leap motion (2022)
Presentation / Conference Contribution

At present, there are about 70 million deaf people using sign language in the world, but for most normal people, it is difficult to understand the meaning of the sign language expression. Therefore, it is of great importance to explore the ways of re... Read More about A modified LSTM model for Chinese sign language recognition using leap motion.

A novel robot skill learning framework based on bilateral teleoperation (2022)
Presentation / Conference Contribution

In this paper, a bilateral teleoperation-based robot skill learning framework is developed to transfer multi-step and contact manipulation skills from humans to robots. Robot skill acquisition via bilateral teleoperation provides a solution for human... Read More about A novel robot skill learning framework based on bilateral teleoperation.

Novel gripper-like exoskeleton design for robotic grasping based on learning from demonstration (2022)
Presentation / Conference Contribution

Learning from demonstration (LfD) has been developed and proved to be a promising method for transferring skill knowledge from human to robot. It is desired to have a demonstration device that can effectively map demonstrations to the robot's motion... Read More about Novel gripper-like exoskeleton design for robotic grasping based on learning from demonstration.

Non-singular fixed-time sliding mode control for unknown-dynamics manipulators interacting with environment (2022)
Presentation / Conference Contribution

In this paper, a robust fixed-time controller is de-signed for manipulators with unknown dynamics while interacting with environment. To realize compliance of the manipulator to the environment, an admittance model is adopted in the system. In the co... Read More about Non-singular fixed-time sliding mode control for unknown-dynamics manipulators interacting with environment.

Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance (2022)
Presentation / Conference Contribution

A fixed-time adaptive neural network control scheme is designed for an unknown model manipulator system with input saturation and external environment disturbance, so that the system convergence time can be parameterized and not affected by the initi... Read More about Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance.

A collaboration scheme for controlling multimanipulator system: A game-theoretic perspective (2022)
Journal Article

In some task-oriented multimanipulator applications, the system not only needs to complete the main assigned tasks, but also should optimize some subobjectives. In order to tap the redundancy potential of individual manipulators and improve the perfo... Read More about A collaboration scheme for controlling multimanipulator system: A game-theoretic perspective.