Abstract. If a mobile robot operates within its environment, it should take other persons into account while moving around. This work presents an approach, which predicts the movements of persons in a very simple way, and uses the predicted trajectories to plan a motion path for the robot. The presented motion prediction and planning process is much faster than real time. A potential field is applied to predict the person’s movement trajectory, and a modified Fast Marching planner is used for the planning process. The aim of this work is, to create an early avoid-ing behavior of the robot, when the robot passes a person, to signal a ”busy”’-behavior towards the person.
This paper presents a novel approach for robot navigation in crowded urban environments where people...
This article proposes a means of autonomous mobile robot navigation in dense crowds based on predict...
“This is a post-peer-review, pre-copyedit version of an article published in Autonomous robots. The ...
Abstract. When mobile robots operate in home environments, a robot should consider the inhabitants w...
Abstract — In order to act socially compliant with humans, mobile robots need to show several behavi...
As people move through their environments, they do not move randomly. Instead, they are often engage...
Human motion prediction is an important feature to improve the path planning of mobile robots. An ...
In various scenarios, e.g. on a construction site, in a shopping mall, or on a street, a mobile robo...
AbstractIn order to effectively plan paths in environments inhabited by humans, robots must accurate...
Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a sha...
For a robot navigating in a human inhabited dynamic environment, the knowledge of how the robot’s mo...
This paper considers the problem of a robot navigating in a crowded or congested environment. A robo...
Mobile, interactive robots that operate in human-centric environments need the capability to safely ...
Over the years, the separate fields of motion planning, mapping, and human trajectory prediction hav...
This paper presents a novel approach for robot navigation in crowded urban environments where people...
This paper presents a novel approach for robot navigation in crowded urban environments where people...
This article proposes a means of autonomous mobile robot navigation in dense crowds based on predict...
“This is a post-peer-review, pre-copyedit version of an article published in Autonomous robots. The ...
Abstract. When mobile robots operate in home environments, a robot should consider the inhabitants w...
Abstract — In order to act socially compliant with humans, mobile robots need to show several behavi...
As people move through their environments, they do not move randomly. Instead, they are often engage...
Human motion prediction is an important feature to improve the path planning of mobile robots. An ...
In various scenarios, e.g. on a construction site, in a shopping mall, or on a street, a mobile robo...
AbstractIn order to effectively plan paths in environments inhabited by humans, robots must accurate...
Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a sha...
For a robot navigating in a human inhabited dynamic environment, the knowledge of how the robot’s mo...
This paper considers the problem of a robot navigating in a crowded or congested environment. A robo...
Mobile, interactive robots that operate in human-centric environments need the capability to safely ...
Over the years, the separate fields of motion planning, mapping, and human trajectory prediction hav...
This paper presents a novel approach for robot navigation in crowded urban environments where people...
This paper presents a novel approach for robot navigation in crowded urban environments where people...
This article proposes a means of autonomous mobile robot navigation in dense crowds based on predict...
“This is a post-peer-review, pre-copyedit version of an article published in Autonomous robots. The ...