6 accepted papers
Conventional human-in-the-loop approaches typically involve users only when a robot encounters failure or uncertainty, treating humans primarily as tools to improve robot performance. However, in many human-centered robotics settings, interaction should support user engagement, keeping users meaning…
Shape control of deformable objects under both rotational and translational deformations is important for versatile robotic applications. However, deformation control with full 6-degree-of-freedom (DoF) manipulation is an open problem, since modeling and describing rotational deformations lead to si
Flexible continuum robots operating in constrained and dynamic environments face significant challenges, especially when interacting with uncertain and potentially unknown conditions. Traditional model-based methods face significant difficulties due to the inherent nonlinearities and uncertainties i
The policy trained via reinforcement learning (RL) makes decisions based on sensor-derived state features. It is common for state features to evolve for reasons such as periodic sensor maintenance or the addition of new sensors for performance improvement. The deployed policy fails in new state spac…
This letter investigates the time-optimal trajectory generation for a six-degrees-of-freedom articulated robot moving along a given parametric path. In the generation procedure, besides the velocity, acceleration, and joint torque, the jerk is also constrained to enhance the smoothness of the robot'
Given a set of outlier-contaminated 2D–3D line correspondences between the scene and a captured image, we aim to recover the absolute camera pose. This is a fundamental problem in computer vision and robotics, for which many methods have been developed and shown impressive performance, but they fail