Pedestrian models for autonomous driving Part I: low-level models, from sensing to tracking
Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …
Socially compliant navigation dataset (scand): A large-scale dataset of demonstrations for social navigation
Social navigation is the capability of an autonomous agent, such as a robot, to navigate in a
“socially compliant” manner in the presence of other intelligent agents such as humans. With …
“socially compliant” manner in the presence of other intelligent agents such as humans. With …
Recent advances in embedding methods for multi-object tracking: a survey
Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …
obtain entire moving trajectories. With the advancement of deep neural networks and the …
Model predictive contouring control for collision avoidance in unstructured dynamic environments
B Brito, B Floor, L Ferranti… - IEEE Robotics and …, 2019 - ieeexplore.ieee.org
This letter presents a method for local motion planning in unstructured environments with
static and moving obstacles, such as humans. Given a reference path and speed, our …
static and moving obstacles, such as humans. Given a reference path and speed, our …
ENRICHME: Perception and Interaction of an Assistive Robot for the Elderly at Home
S Coşar, M Fernandez-Carmona, R Agrigoroaie… - International Journal of …, 2020 - Springer
Recent technological advances enabled modern robots to become part of our daily life. In
particular, assistive robotics emerged as an exciting research topic that can provide …
particular, assistive robotics emerged as an exciting research topic that can provide …
Online learning for 3D LiDAR-based human detection: experimental analysis of point cloud clustering and classification methods
This paper presents a system for online learning of human classifiers by mobile service
robots using 3D LiDAR sensors, and its experimental evaluation in a large indoor public …
robots using 3D LiDAR sensors, and its experimental evaluation in a large indoor public …
Online learning for human classification in 3D LiDAR-based tracking
Z Yan, T Duckett, N Bellotto - 2017 IEEE/RSJ International …, 2017 - ieeexplore.ieee.org
Human detection and tracking are essential aspects to be considered in service robotics, as
the robot often shares its workspace and interacts closely with humans. This paper presents …
the robot often shares its workspace and interacts closely with humans. This paper presents …
3DOF pedestrian trajectory prediction learned from long-term autonomous mobile robot deployment data
This paper presents a novel 3DOF pedestrian trajectory prediction approach for autonomous
mobile service robots. While most previously reported methods are based on learning of 2D …
mobile service robots. While most previously reported methods are based on learning of 2D …
Thör: Human-robot navigation data collection and accurate motion trajectories dataset
Understanding human behavior is key for robots and intelligent systems that share a space
with people. Accordingly, research that enables such systems to perceive, track, learn and …
with people. Accordingly, research that enables such systems to perceive, track, learn and …
[HTML][HTML] Social navigation framework for assistive robots in human inhabited unknown environments
In human-populated environments, robot navigation requires more than mere obstacle
avoidance for safe and comfortable human-robot interaction. Socially aware navigation …
avoidance for safe and comfortable human-robot interaction. Socially aware navigation …