A precondition for a mobile robot to autonomously explore its environment is the ability to self-localise. When a map of the environment is not available, the robot should be able to self-localise and, at the same time, to build a representation of the environment. Here the problem: position estimation needs an environment model, and world modelling needs the robot position. Current research proposes solutions based on the simultaneous execution of the two activities. We propose a novel approach based on their concurrent execution. This approach, titled CLAM (Concurrent Localisation And Mapping), is founded on the conjecture that a proper separation of concerns may help in breaking the loop of the problem. Localisation and Modelling, acting on different time scales, are mostly independent each other. When a synchronisation is needed, it is controlled by an external and suitable strategy. Finally we are testing our approach by exploiting the Real-Time Performers framework based on a new set of architectural abstractions modelling the temporal behaviour of a system.

Micucci, D., Marchese, F., Sorrenti, D., Tisato, F. (2004). CLAM: a Time-Sensitive Approach to Mobile Robot Localisation And Mapping. In WIP session of the 10th IEEE Real-Time and Embedded Technology and Application (RTAS).

CLAM: a Time-Sensitive Approach to Mobile Robot Localisation And Mapping

MICUCCI, DANIELA;MARCHESE, FABIO MARIO GUIDO;SORRENTI, DOMENICO GIORGIO;TISATO, FRANCESCO
2004

Abstract

A precondition for a mobile robot to autonomously explore its environment is the ability to self-localise. When a map of the environment is not available, the robot should be able to self-localise and, at the same time, to build a representation of the environment. Here the problem: position estimation needs an environment model, and world modelling needs the robot position. Current research proposes solutions based on the simultaneous execution of the two activities. We propose a novel approach based on their concurrent execution. This approach, titled CLAM (Concurrent Localisation And Mapping), is founded on the conjecture that a proper separation of concerns may help in breaking the loop of the problem. Localisation and Modelling, acting on different time scales, are mostly independent each other. When a synchronisation is needed, it is controlled by an external and suitable strategy. Finally we are testing our approach by exploiting the Real-Time Performers framework based on a new set of architectural abstractions modelling the temporal behaviour of a system.
No
paper
robot, autonomous, software architecture, time
English
IEEE Real-Time and Embedded Technology and Application (RTAS)
http://www.cs.virginia.edu/rtas04/wip/wip16.pdf
Micucci, D., Marchese, F., Sorrenti, D., Tisato, F. (2004). CLAM: a Time-Sensitive Approach to Mobile Robot Localisation And Mapping. In WIP session of the 10th IEEE Real-Time and Embedded Technology and Application (RTAS).
Micucci, D; Marchese, F; Sorrenti, D; Tisato, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/27414
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