2 research outputs found
Markerless Visual Robot Programming by Demonstration
In this paper we present an approach for learning to imitate human behavior
on a semantic level by markerless visual observation. We analyze a set of
spatial constraints on human pose data extracted using convolutional pose
machines and object informations extracted from 2D image sequences. A scene
analysis, based on an ontology of objects and affordances, is combined with
continuous human pose estimation and spatial object relations. Using a set of
constraints we associate the observed human actions with a set of executable
robot commands. We demonstrate our approach in a kitchen task, where the robot
learns to prepare a meal.Comment: 6 pages, 5 figures, 3rd BAILAR worksho
Trends, Challenges and Adopted Strategies in RoboCup@Home
Scientific competitions are crucial in the field of service robotics. They
foster knowledge exchange and allow teams to test their research in
unstandardized scenarios and compare result. Such is the case of RoboCup@Home.
However, keeping track of all the technologies and solution approaches used by
teams to solve the tests can be a challenge in itself. Moreover, after eleven
years of competitions, it's easy to delve too much into the field, losing
perspective and forgetting about the user's needs and long term goals.
In this paper, we aim to tackle this problems by presenting a summary of the
trending solutions and approaches used in RoboCup@Home, and discussing the
attained achievements and challenges to overcome in relation with the progress
required to fulfill the long-term goal of the league. Hence, considering the
current capabilities of the robots and their limitations, we propose a set of
milestones to address in upcoming competitions.
With this work we lay the foundations towards the creation of roadmaps that
can help to direct efforts in testing and benchmarking in robotics
competitions.Comment: 18 pages, 7 figures, 3 table