Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …

This paper provides a comprehensive review of the current status, advancements, and future
prospects of humanoid robots, highlighting their significance in driving the evolution of next …

Robot learning through kinesthetic teaching is a promising way of cloning human behaviors,
but it has its limits in the performance of complex tasks with small amounts of data, due to …

Recent advancement in vision‐based robotics and deep‐learning techniques has enabled
the use of intelligent systems in a wider range of applications requiring object manipulation …

The use of social robots in service scenarios (eg in hotels) is expected to increase.
Research has indicated that realistic threat and identity threat contribute to prejudice …

In recent decades, there has been an increasing interest in the use of robotic powered
exoskeletons to assist patients with movement disorders in rehabilitation and daily life …

Machine vision-based planar grasping detection is challenging due to uncertainty about
object shape, pose, size, etc. Previous methods mostly focus on predicting discrete gripper …

Owing to its potential superiorities in terms of flexibility, compliance, and robustness, the
musculoskeletal robotic system has become a promising direction for next-generation …

Transferring human stiffness regulation strategies to robots enables them to effectively and
efficiently acquire adaptive impedance control policies to deal with uncertainties during the …

Hierarchical reinforcement learning (HRL) can learn the decomposed subpolicies
corresponding to the local state-space; therefore, it is a promising solution to complex …