Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics
applications such as self-driving cars. Existing motion planning methods become ineffective …

Real-world planning problems often involve hundreds or even thousands of objects,
straining the limits of modern planners. In this work, we address this challenge by learning to …

A detailed survey of the available literature on path planning of Autonomous Ground Vehicle
(AGV) is conducted, including the overview of single-robot control architectures, different …

In robotics and video games, one often discretizes continuous terrain into a grid with blocked
and unblocked grid cells and then uses path-planning algorithms to find a shortest path on …

This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …

Mobile robots that encounter people on a regular basis must react to them in some way.
While traditional robot control algorithms treat all unexpected sensor readings as objects to …

Real-time situated agents, such as characters in real-time computer games, often do not
know the terrain in advance but automatically observe it within a certain range around …

This chapter provides a round picture of the development and advances in the field of
evolving fuzzy systems (EFS) made during the last decade since their first appearance in …

In this paper, we address the problem of distributed path planning for large teams of
hundreds of robots in constrained environments. We introduce two distributed prioritized …

Compressed sensing is a develo** field aiming at the reconstruction of sparse signals
acquired in reduced dimensions, which make the recovery process under-determined. The …