This paper is intended to pave the way for new researchers in the field of robotics and
autonomous systems, particularly those who are interested in robot localization and …

Advances in display and tracking technologies hold the promise of increasingly immersive
augmented-reality experiences. Unfortunately, the on-demand generation of haptic …

Point clouds registration is an important step for laser scanner data processing, and there
have been numerous methods. However, the existing methods often suffer from low …

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive
measurements. Advances in range imaging technologies enable the rapid acquisition of …

We propose a new color-and-depth general visual object tracking benchmark (CDTB).
CDTB is recorded by several passive and active RGB-D setups and contains indoor as well …

We present a three-level cognitive system in a learning by demonstration context. The
system allows for learning and transfer on the sensorimotor level as well as the planning …

This study proposes a 3D global localization method that implements mobile LiDAR
map** and point cloud registration to recognize the locations of objects in an underground …

Purpose–The purpose of this paper is to propose a new algorithm based on programming
by demonstration and exception strategies to solve assembly tasks such as peg-in-hole …

Abstract Model-based reinforcement learning is a powerful paradigm for learning tasks in
robotics. However, in-depth exploration is usually required and the actions have to be …

This paper proposes and evaluates a pipeline to automatically register point clouds
captured by depth sensors like the Microsoft Kinect. The method neither makes assumptions …