0000000000082981
AUTHOR
Stephen Balakirsky
showing 4 related works from this author
Ontology-based state representations for intention recognition in human–robot collaborative environments
2013
In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level state relationships that must be true for future actions to occur, a robot can use the detailed state information described in this paper to infer the probability of subsequent actions occurring. This would allow the robot to better help the …
3D Reconstruction of rough terrain for USARSim using a height-map method
2008
In this paper, a process for a simplified reconstruction of rough terrains from point clouds acquired using laser scanners is presented. The main idea of this work is to build height-maps which are level gray-scale images representing the ground elevation. These height-maps are generated from step-fields which can be represented by a set of side-by-side pillars. Although height-maps are a practical means for rough terrain reconstruction, it is not possible to represent two different elevations for a given location with one height-map. This is an important drawback as terrain point clouds can show different zones representing surfaces above other surfaces.In this paper, a methodology to crea…
Ontology-based state representation for intention recognition in cooperative human-robot environments
2012
In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the detailed state information presented in this paper to infer the probability of subsequent actions occurring. This would enable the robot to better help th…
Performance evaluation of robotic knowledge representation (PERK)
2012
In this paper, we explore some ways in which symbolic knowledge representations have been evaluated in the past and provide some thoughts on what should be considered when applying and evaluating these types of knowledge representations for real-time robotics applications. The emphasis of this paper is that the robotic applications require real-time access to information, which has not been one of the aspects measured in traditional symbolic representation evaluation approaches.