A novel algorithm for collision-free navigation of a mobile robot on the campus road with
pedestrian roaming is described in this paper. Proposed method uses the RGB-D depth …

Safety is the most important to the mobile robots that coexist with human. There are many
studies that investigate obstacle detection and collision avoidance by predicting obstacles' …

We present a mobile robot navigation system guided by a novel vision-based road
recognition approach. The system represents the road as a set of lines extrapolated from the …

Predicting pedestrian movements remains a complex and persistent challenge in robot
navigation research. We must evaluate several factors to achieve accurate predictions, such …

This study designed, developed, and evaluated a deep-learning-based companion robot
prototype for indoor navigation and obstacle avoidance using an RGB-D camera as the sole …

We present a novel algorithm for safe navigation of a mobile robot in uncertain environment
among pedestrians. Our approach uses commodity visual sensors, including monocamera …

In this paper, an improved path planning algorithm with two stages is proposed for indoor
mobile robots to help them navigate across dynamic crowded areas. First, an environmental …

Being able to avoid obstacles and pedestrians in particular, is essential for robots to function
in dynamic environments. In contrast with model based methods utilizing primarily computer …

This paper introduces a general framework for detection, recognition, and tracking
preceding vehicles and pedestrians based on a deep learning approach. The proposed …

The thesis at hand is concerned with robots' navigation in human crowds. Specifically,
methods are developed for planning a mobile robot's local motion between pedestrians, and …