We benchmark the robustness of maximum likelihood based uncertainty estimation methods
to outliers in training data for regression tasks. Outliers or noisy labels in training data results …

With the rapid development of data‐driven techniques, data has played an essential role in
various computer vision tasks. Many realistic and synthetic datasets have been proposed to …

This paper presents a vision-based approach for estimating the configuration of, and
providing control signals for, an under-sensored robot manipulator using a single monocular …

Kinematic structures are very common in the real world. They range from simple articulated
objects to complex mechanical systems. However, despite their relevance, most model …

In recent years, the effective and safe collaboration between humans and machines has
gained significant importance, particularly in the Industry 4.0 scenario. A critical prerequisite …

Robots working in everyday and unstructured environments will need to perform
manipulation skills using different sets of objects. To determine if a manipulation skill can be …

One of the problems with industrial robots is their ability to accurately locate the pose of the
end‐effector. Over the years, many other solutions have been studied including static …

Autonomous manipulation systems operating in domains where human intervention is
difficult or impossible (eg, underwater, extraterrestrial or hazardous environments) require a …

A parallel algorithm for terrain generation based on CUDA architecture is proposed in this
paper, which aims to address the problems of high computational load and low efficiency …

IoT devices suffer from resource limitations, such as processor, RAM, and disc storage.
These limitations become more evident when handling demanding applications, such as …