The significant power of deep learning networks has led to enormous development in object
detection. Over the last few years, object detector frameworks have achieved tremendous …

We propose a decentralized variant of Monte Carlo tree search (MCTS) that is suitable for a
variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimize …

Thanks to the efforts of the robotics and autonomous systems community, the myriad
applications and capacities of robots are ever increasing. There is increasing demand from …

We present a new approach to long-term mobile robot map** in dynamic indoor
environments. Unlike traditional world models that are tailored to represent static scenes …

Over the last few years, novel color and depth sensors have pushed the boundaries of robot
perception significantly. Today, several new depth-sensing products are replacing the …

Robots that are operating for extended periods of time need to be able to deal with changes
in their environment and represent them adequately in their maps. In this paper, we present …

Abstract Service robots are appearing more and more in our daily life. The development of
service robots combines multiple fields of research, from object perception to object …

Robotic perception is related to many applications in robotics where sensory data and
artificial intelligence/machine learning (AI/ML) techniques are involved. Examples of such …

Robots need to have a memory of previously observed, but currently occluded objects to
work reliably in realistic environments. We investigate the problem of encoding object …

This letter presents a novel method for introducing time into discrete and continuous spatial
representations used in mobile robotics, by modeling long-term, pseudo-periodic variations …