Semantic Perception, Mapping and Exploration
Semantic perception for intelligent systems and robots remains an
active area of research with many recent advances that address a
variety of problems. One key requirement that these systems have is to
reason in
spaces exceeding their local perceptual space. For example, a personal
robot operating in human living spaces needs to continuously acquire
and semantically understand perceptual information while maintaining
an
accurate internal representation of the environment that may change
over time.
The main focus of this special issue is on the autonomous acquisition
of semantic information in intelligent robots and systems, as well as
the use of semantic knowledge to guide further acquisition of
information from the environment. The performance of robotic systems
can significantly be improved by incorporating semantic information.
We are looking for research papers that aim at building bindings from
raw sensor output, i.e., sub-symbolic data like 3-d point clouds, to
knowledge representations, i.e., symbols e.g., parametric 3-d models.
Topics of interest include, but are not necessarily limited to:
- Semantic robot vision and scene interpretation for mobile manipulation
- Segmentation and annotation of natural scenes (e.g., from images or point clouds)
- Exploration strategies for semantic mapping and knowledge acquisition
- Semantic approaches for long-term operation in dynamic environments
- Ontologies and efficient representations for managing semantic information in robotics
- Use of semantic information in mapping (e.g., registration of sensory information) or knowledge acquisition
Guest Editors:
- Dirk Holz, Autonomous Intelligent Systems Group, University of Bonn, Germany
- Daniel Munoz, Carnegie Mellon University, USA
- Andreas Nuechter, Jacobs University Bremen gGmbH, Germany (Managing Guest Editor)
- Radu Bogdan Rusu, Willow Garage, USA
Other Important Dates:
- Reviews sent to contributers: November 11, 2011
- Notifications sent to authors: March 13, 2012
- PUBLICATION: Mid-2012