As personalization technology increasingly orchestrates individualized shopping or
marketing experiences in industries such as logistics, fast-moving consumer goods, and …

Multi-sensor based motion tracking is of great interest to the robotics community as it may
lessen the need for expensive optical motion capture equipment. However, the traditional …

While robotic tactile sensors have been developed to help robots to perceive and interact
effectively with their surrounding environment by mimicking the structure and function of …

Recent research work has demonstrated that pregrasp tactile information can be used to
effectively predict whether a grasp will be successful or not. However, most of the existing …

Performing dexterous tasks with a multi fingered robotic hand remains challenging. Tactile
sensors provide touch states and object features for multifingered tasks, yet the variety in …

In order to improve the accuracy of manipulator operation, it is necessary to install a tactile
sensor on the manipulator to obtain tactile information and accurately classify a target …

Current issues with neuromorphic visual–tactile perception include limited training network
representation and inadequate cross-modal fusion. To address these two issues, we …

In this paper, we probe the proficiency of contrastive learning techniques in forecast grasp
outcomes, without supervision. Employing a dataset that's open to the public, we establish …

How to solve the problem of continual learning of robotic tactile perception in an open,
dynamic environment is a pressing task. Although continual learning has been extensively …

The classification of grasping states is crucial for robots' stable operations that based on its
real-timely results, the robot can adjust the appropriate gripping force. However, until now …