Human navigation is facilitated through the association of actions with landmarks, tapping
into our ability to recognize salient features in our environment. Consequently, navigational …

Deep reinforcement learning-based approaches to mapless navigation have relied on the
distance to the goal state being known a priori or that the distance to the goal can be …

Interestingness recognition is crucial for decision making in autonomous exploration for
mobile robots. Previous methods proposed an unsupervised online learning approach that …

In this paper, we address a recent trend in robotic home appliances to include vision
systems on personal devices, capable of personalizing the appliances on the fly. In …

In this paper, we introduce a novel methodology for fusing sensors and improving
robustness to sensor failures in end-to-end learning based autonomous navigation of …

Autonomous mapless navigation is very challenging since it is difficult to effectively find the
way without a map. In this article, we address a problem encountered when realizing …

Inspired by the discoveries in neuroscience, the method of visual place recognition develops
toward using multiple homogenous spatial scales. We present a novel multi-scale place …

A Hopfield-type neural networks (HNN) algorithm associated with histogram navigation
method is proposed in this paper for real-time map building and path planning for multiple …

Learning to recognize new objects in real time in unconstrained environments presents
significant challenges for robotic platforms. We present a meta-learning solution to this …

Drivable area understanding is an essential problem in the fields of robot autonomous
navigation. Mobile robots or other autonomous vehicles need to perceive their surrounding …