MAP

Classification, Sensor Fusion, and Tracking

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The MAP (MAP Anchors Perceptions) module allows to build the environment model on the basis of the data acquired through sensors. MAP contains a hierarchical conceptual model, in which are specified the classes of objects that can be perceived. The anchoring process is divided into three phases:

  1. Classification
  2. Merging
  3. Tracking
Anchoring process

In the classification phase (carried out by the TIGER sub-module), MAP receives from sensors descriptions of perceived objects in terms of percepts (symbolic features), and identifies the concept that has the best matching degree. At the end of the classification phase, the TIGER produces the conceptual instances related to the perceived objects and their degree of reliability.

Since the same physical object may be perceived at the same time by distinct sensors, the output of the TIGER may contain several conceptual instances that are related to the same physical object. In the merging phase, the FUSION sub-module merges those conceptual instances that are supposed to be originated from the perception of the same object by different sensors.

The tracking phase of anchoring consists of maintaining in time a coherent state of the model and a correct classification of instances. This phase tries to match the conceptual instances perceived in the past with those generated by the latest perception (data association). Then, the dynamic properties of the conceptual instances are updated through Kalman filtering.

This approach is well suited for multi-agent domains. It is expected that in a multi--agent context each agent could take advantage of data perceived by its teammates. In fact, each agent can be seen as an intelligent sensor that, instead of producing features, generates conceptual instances that can be processed directly by the FUSION sub-module of another agent.

Principal investigators
M. Matteucci, M. Restelli

Research contributors
A. Bonarini,...

Related Papers


  1. Bonarini, A., Matteucci M., Restelli M. (2001) Anchoring: do we need new solutions to an old problem or do we have old solutions for a new problem? Proceedings of the AAAI Fall Symposium on Anchoring Symbols to Sensor Data in Single and Multiple Robot Systems, AAAI Press, Menlo Park, CA, 79-86.

  2. Bonarini, A., Matteucci, M. and Restelli, M. (2001) A framework for robust sensing in multi--agent systems. In A. Birk, S. Coradeschi (Eds.) RoboCup 2001--Robot Soccer World Cup V, Lecture Notes in Computer Science, Springer Verlag, Berlin, D.

 

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