9 accepted papers
In this paper we present a system capable of collecting and annotating, human performed, robot understandable, everyday activities from virtual environments. The human movements are mapped in the simulated world using off-the-shelf virtual reality devices with full body, and eye tracking capabilitie…
In this paper, we present an approach and an implemented pipeline for transferring data acquired from observing humans in virtual environments onto robots acting in the real world, and adapting the data accordingly to achieve successful task execution. We demonstrate our pipeline by inferring seven…
In this paper, we will describe AMEvA (Automated Models of Everyday Activities), a special-purpose knowledge acquisition, interpretation, and processing system for human everyday manipulation activity that can automatically: (1) create and simulate virtual human living and working environments (such…
With the advancements in robotic technology and the progress in human-robot interaction research, the interest in deploying mixed human-robot teams in rescue missions is increasing. Due to their complementary capabilities in terms of locomotion, visibility and reachability of areas, human-robot team…
In this paper we present KnowRob2, a second generation knowledge representation and reasoning framework for robotic agents. KnowRob2 is an extension and partial redesign of KnowRob, currently one of the most advanced knowledge processing systems for robots that has enabled them to successfully perfo…
AI knowledge representation and reasoning methods consider actions to be blackboxes that abstract away from how they are executed. This abstract view does not suffice for the decision making capabilities required by robotic agents that are to accomplish manipulation tasks. Such robots have to reason…
To properly perform tasks based on abstract instructions, autonomous robots need refined reasoning skills in order to bridge the gap between the ambiguous descriptions and the comprehensive information needed to execute the implied actions. In this article, we present an automated knowledge acquisit…
In this paper we discuss how the combination of modern technologies in “big data” storage and management, knowledge representation and processing, cloud-based computation, and web technology can help the robotics community to establish and strengthen an open research discipline. We describe how we m
Predicting the outcome of an action can help a robot detect failures in advance, and schedule action replanning before an error occurs. We propose using an interactive physics based simulator with the aim of collecting realistic data to be used for learning. We then show how we save and query for sp…