Abstract Simultaneous Localization and Mapping (SLAM) is a key problem in the field of
Artificial Intelligence and mobile robotics that addresses the problem of localization and …

Mapping is a crucial task in robotics and a fundamental building block of most mobile
systems deployed in the real world. Robots use different environment representations …

Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors
are often corrupted in those complicated and large-scale environments. This article …

Building datasets for autonomous vehicles has become an essential element of robotics
research. Numerous datasets were published, pushing the state-of-the-art forward. This …

In robotics, spiking neural networks (SNNs) are increasingly recognized for their largely
unrealized potential energy efficiency and low latency particularly when implemented on …

In the paper a solution for building of 3D map of unknown terrain for the purposes of control
of wheeled autonomous mobile robots operating in an isolated and hard-access area is …

This letter introduces Wolf, a C++ estimation framework based on factor graphs and targeted
at mobile robotics. Wolf can be used beyond SLAM to handle self-calibration, model …

The ability to produce large-scale maps for nav-igation, path planning and other tasks is a
crucial step for autonomous agents, but has always been challenging. In this work, we …

Robotic mobile platforms are key building blocks for numerous applications and cooperation
between robots and humans is a key aspect to enhance productivity and reduce labor cost …

Abstract Most commercially available Light Detection and Ranging (LiDAR) s measure the
distances along a 2D section of the environment by sequentially sampling the free range …