Robert Eidenberger, Josef Scharinger,
"Active Perception and Scene Modeling by Planning with Probabilistic 6D Object Poses"
: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Seite(n) 136 - 143, 1-2010
Original Titel:
Active Perception and Scene Modeling by Planning with Probabilistic 6D Object Poses
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
Original Kurzfassung:
This paper presents an approach to probabilistic
active perception planning for scene modeling in cluttered
and realistic environments. When dealing with complex, multiobject
scenes with arbitrary object positions, the estimation of
6D poses including their expected uncertainties is essential. The
scene model keeps track of the probabilistic object hypotheses
over several sequencing sensing actions to represent the real
object constellation.
To improve detection results and to tackle occlusion problems
a method for active planning is proposed which reasons about
model and state transition uncertainties in continuous and highdimensional
domains. Information theoretic quality criteria are
used for sequential decision making to evaluate probability
distributions. The probabilistic planner is realized as a partially
observable Markov decision process (POMDP).
The active perception system for autonomous service robots
is evaluated in experiments in a kitchen environment. In 80 test
runs the efficiency and satisfactory behavior of the proposed
methodology is shown in comparison to a random and a stepaside
action selection strategy. The objects are selected from a
large database consisting of 100 different household items.
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