Touch sensing can help robots understand their surrounding environment, and in particular
the objects they interact with. To this end, roboticists have, in the last few decades …

Over the last two decades, considerable scientific and technological efforts have been
devoted to develo** tactile sensing based on a variety of transducing mechanisms, with …

Multi-modality image fusion is an effective technique to fuse the complementary information
from multi-modality images into an integrated image. The additional information can not only …

With the rapid development of machine learning, its powerful function in the machine vision
field is increasingly reflected. The combination of machine vision and robotics to achieve the …

Multimodality image fusion is the hot topic in medical imaging field which increases the
clinical diagnosis accuracy through fusing complementary information of multimodality …

The robotic grasp detection is a great challenge in the area of robotics. Previous work mainly
employs the visual approaches to solve this problem. In this paper, a hybrid deep …

In view of the long execution time and low execution efficiency of Support Vector Machine in
large-scale training samples, the paper has proposed the online incremental and …

The camera provides rich visual information regarding objects and becomes one of the most
mainstream sensors in the automation community. However, it is often difficult to be …

Recent research has shown the speed advantage of extreme learning machine (ELM) and
the accuracy advantage of sparse representation classification (SRC) in the area of image …

Road detection is one of the key challenges for autonomous vehicles. Two kinds of sensors
are commonly used for road detection: cameras and LIDARs. However, each of them suffers …