State-of-the-art navigation methods leverage a spatial memory to generalize to new
environments, but their occupancy maps are limited to capturing the geometric structures …

Abstract Purpose of Review Multi-robot exploration—ie, the problem of mapping unknown
features of an environment—is fundamental in many tasks, including search and rescue …

A crucial ability of mobile intelligent agents is to integrate the evidence from multiple sensory
inputs in an environment and to make a sequence of actions to reach their goals. In this …

We consider the problem of Vision-and-Language Navigation (VLN). The majority of current
methods for VLN are trained end-to-end using either unstructured memory such as LSTM, or …

We address the problem of efficient 3-D exploration in indoor environments for micro aerial
vehicles with limited sensing capabilities and payload/power constraints. We develop an …

We consider the problems of exploration and pointgoal navigation in previously unseen
environments, where the spatial complexity of indoor scenes and partial observability …

In real-world environments, ranging from urban disastrous scenes to underground mining
tunnels, autonomous mobile robots are being deployed in harsh and cluttered …

Vision-based prediction algorithms have a wide range of applications including autonomous
driving, surveillance, human-robot interaction, weather prediction. The objective of this …

This study presents a novel octree‐based three‐dimensional (3D) exploration and coverage
method for autonomous underwater vehicles (AUVs). Robotic exploration can be defined as …

Mobile robots capable of navigating seamlessly and safely in pedestrian rich environments
promise to bring robotic assistance closer to our daily lives. In this paper we draw on insights …