Grid maps, especially occupancy grid maps, are ubiquitous in many mobile...
Accurate maps are a prerequisite for virtually all autonomous vehicle ta...
Most state-of-the-art data-driven grasp sampling methods propose stable ...
Localization of autonomous unmanned aerial vehicles (UAVs) relies heavil...
Mapping people dynamics is a crucial skill, because it enables robots to...
Knowing the position and orientation of an UAV without GNSS is a critica...
Localization of low-cost unmanned aerial vehicles(UAVs) often relies on
...
While 2D occupancy maps commonly used in mobile robotics enable safe
nav...
Recent advances in multi-fingered robotic grasping have enabled fast
6-D...
While there exists a large number of methods for manipulating rigid obje...
Creating and maintaining an accurate representation of the environment i...
Accurately modeling local surface properties of objects is crucial to ma...
Among the various options to estimate uncertainty in deep neural network...
The most common way for robots to handle environmental information is by...
Modern intelligent and autonomous robotic applications often require rob...
Current end-to-end grasp planning methods propose grasps in the order of...
We present a method for planning robust grasps over uncertain shape comp...
Estimating the uncertainty of predictions is a crucial ability for robot...
Many mobile robots rely on 2D laser scanners for localization, mapping, ...
RX Detector is recognized as the benchmark algorithm for image anomaly
d...