Outputs (5)

Handheld device design for robotic teleoperation based on multi-sensor fusion (2023)
Presentation / Conference Contribution

Precise leader-follower control is critical for teleop- eration. This paper designs and implements a low-cost leader device for unilateral teleoperation scenario. Monocular vision based on fiducial markers and MEMS Inertial Measurement Unit (IMU) are... Read More about Handheld device design for robotic teleoperation based on multi-sensor fusion.

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.

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.

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 novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use (2022)
Presentation / Conference Contribution

Dynamic Movement Primitives (DMPs) is a general method for learning skills from demonstrations. Most previous research on DMP has focused on point to point skill learning and training, and the skills learned are usually generalized based on the same... Read More about A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use.