11 accepted papers
Accurate depth maps are essential for robotic grasping. However, transparent objects often cause depth cameras to produce missing or distorted depth due to reflection and refraction, making grasping them particularly challenging. Precise depth estimation for transparent objects is therefore crucial.
Spatio-temporal alignment is crucial for temporal modeling of end-to-end (E2E) perception in autonomous driving (AD), providing valuable structural and textural prior information. Existing methods typically rely on the attention mechanism to align objects across frames, simplifying the motion model
In this letter, we present a high-rate and robust multi-sensor fusion framework for state estimation of humanoid robots, named HR<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>-KIL
In this work, a multimodal point cloud registration method using CT and video frames is proposed to optimize the modeling of the bronchial cavity environment. Preoperative CT data improve the quality of point clouds acquired from intraoperative video frames. Initially, preoperative CT scans are used
Performing acrobatic maneuvers like dynamic jumping in bipedal robots presents significant challenges in terms of actuation, motion planning, and control. Traditional approaches to these tasks often simplify dynamics to enhance computational efficiency, potentially overlooking critical factors such
Recently, reinforcement learning (RL) is often used for learning the strategy of peg-in-hole tasks. However, traditional state representation of PiH RL might be either redundant or abstract, which leads to unnecessary learning steps and incompatibility with mathematical training optimization. To iss
Monocular depth estimation has been actively studied in fields such as robot vision, autonomous driving, and 3D scene understanding. Given a sequence of color images, unsupervised learning methods based on the framework of Structure-From-Motion (SfM) simultaneously predict depth and camera relative…
The sampling-based partial motion planning algorithm has come into widespread application in dynamic mobile robot navigation due to its low calculation costs and excellent performance in avoiding obstacles. However, when confronted with complicated scenarios, the motion planning algorithms are easil…
To achieve more intelligent performance for walking-assistive devices, spontaneous motion intention of walking speed should be identified for providing a control command. In this letter, cerebral hemoglobin information was analyzed to recognize three levels of walking speed: low, medium, and high sp
It is of great importance to pick up a single carbon nanotube (CNT) from a bulk of CNTs for nanodevice fabrication. In this study, we have proposed a nanorobotic manipulation system allowing automated pick-up of CNTs based on visual feedback. We utilize histogram normalization for automatic binariza…