25-07-2012, 01:03 PM
An Autonomous Mobile Robotic System for Surveillance of Indoor Environments
[attachment=28866]
Abstract:
The development of intelligent surveillance systems is an active research area. In this context, mobile
and multi-functional robots are generally adopted as means to reduce the environment structuring and the
number of devices needed to cover a given area. Nevertheless, the number of different sensors mounted on the
robot, and the number of complex tasks related to exploration, monitoring, and surveillance make the design of the
overall system extremely challenging. In this paper, we present our autonomous mobile robot for surveillance of
indoor environments. We propose a system able to handle autonomously general-purpose tasks and complex
surveillance issues simultaneously. It is shown that the proposed robotic surveillance scheme successfully
addresses a number of basic problems related to environment mapping, localization and autonomous navigation,
as well as surveillance tasks, like scene processing to detect abandoned or removed objects and people detection
and following. The feasibility of the approach is demonstrated through experimental tests using a multisensor
platform equipped with a monocular camera, a laser scanner, and an RFID device. Real world applications of the
proposed system include surveillance of wide areas (e.g. airports and museums) and buildings, and monitoring of
safety equipment.
Introduction
The increasing need for automated surveillance of indoor
environments, such as airports, warehouses, production
plants, etc. has stimulated the development of intelligent
systems based on mobile sensors. Differently from
traditional non-mobile surveillance devices, those based
on mobile robots are still in their initial stage of
development, and many issues are currently open for
investigation (Everett, H., 2003), (DehuaI, Z. et al. 2007).
The use of robots significantly expands the potential of
surveillance systems, which can evolve from the
traditional passive role, in which the system can only
detect events and trigger alarms, to active surveillance, in
which a robot can be used to interact with the
environment, with humans or with other robots for more
complex cooperative actions (Burgard, W. et al. 2000),
(Vig, L. & Adams, J.A., 2007).
System Overview
This section describes the three-layer architecture
developed for the surveillance system. The component
layout, depicted in Fig. 1, reveals the modular nature of
the system. We propose a reconfigurable componentbased
approach in which the three main components can
be viewed as containers of dynamic libraries that can be
configured for the particular scenario. More specifically
we can select what primitive behaviors (e.g. avoid
obstacles, wandering, go forward, etc.), complex tasks
(e.g. robot localization with RFID and vision, detect
removed or abandoned objects, detect people, etc.) and
control algorithms (e.g. event detection, task sequencing,
human operator interaction, etc.) have to start.
To obtain this reconfigurable scheme a key role is played
by the sensory data management sub-system. Each of the
three main components, i.e. controller, executor, and
supervisor, is connected with the sensory input. This
information is used in different ways: at the highest level,
sensory data are converted into events, which are used to
control task executions; at the middle level, sensory data
are used to monitor and control the execution of the task in
progress; finally, at the lowest level, sensory inputs are
used by active behaviors to perform the associated actions.
Surveillance Tasks: Object and People Detection
In this section, specific surveillance tasks are described.
The main purpose of these tasks is to obtain information
about environment changes in a predetermined area. In
particular, we have developed two different classes of
tasks, using a multisensor approach. The first one
monitors the position of predefined objects or the
presence of new ones, whereas the second one detects the
presence of intruders reacting with predefined actions
(e.g. following the person).
Discussion and Conclusion
In this paper, we presented the implementation and
integration of several autonomous navigation and
surveillance functions on a multisensor mobile robot for
robotic site monitoring tasks.
The major aim of the paper was that of providing a
comprehensive overview of the system, as well as
experimental results in real contexts, in order to show the
feasibility of the proposed methods in real-world
situations.
First, we described the architecture of the system based
on a three-layer scheme that allows for modularity and
flexibility, and may supervise a number of basic
navigation tasks and specific surveillance tasks. The
control system makes the robot able to execute
autonomously multiple heterogeneous task sequences in
dynamic environments, since it models the sequential
constraints of the tasks, defines the priority among tasks
and dynamically selects the most appropriate behaviors
in any given circumstance.
[attachment=28866]
Abstract:
The development of intelligent surveillance systems is an active research area. In this context, mobile
and multi-functional robots are generally adopted as means to reduce the environment structuring and the
number of devices needed to cover a given area. Nevertheless, the number of different sensors mounted on the
robot, and the number of complex tasks related to exploration, monitoring, and surveillance make the design of the
overall system extremely challenging. In this paper, we present our autonomous mobile robot for surveillance of
indoor environments. We propose a system able to handle autonomously general-purpose tasks and complex
surveillance issues simultaneously. It is shown that the proposed robotic surveillance scheme successfully
addresses a number of basic problems related to environment mapping, localization and autonomous navigation,
as well as surveillance tasks, like scene processing to detect abandoned or removed objects and people detection
and following. The feasibility of the approach is demonstrated through experimental tests using a multisensor
platform equipped with a monocular camera, a laser scanner, and an RFID device. Real world applications of the
proposed system include surveillance of wide areas (e.g. airports and museums) and buildings, and monitoring of
safety equipment.
Introduction
The increasing need for automated surveillance of indoor
environments, such as airports, warehouses, production
plants, etc. has stimulated the development of intelligent
systems based on mobile sensors. Differently from
traditional non-mobile surveillance devices, those based
on mobile robots are still in their initial stage of
development, and many issues are currently open for
investigation (Everett, H., 2003), (DehuaI, Z. et al. 2007).
The use of robots significantly expands the potential of
surveillance systems, which can evolve from the
traditional passive role, in which the system can only
detect events and trigger alarms, to active surveillance, in
which a robot can be used to interact with the
environment, with humans or with other robots for more
complex cooperative actions (Burgard, W. et al. 2000),
(Vig, L. & Adams, J.A., 2007).
System Overview
This section describes the three-layer architecture
developed for the surveillance system. The component
layout, depicted in Fig. 1, reveals the modular nature of
the system. We propose a reconfigurable componentbased
approach in which the three main components can
be viewed as containers of dynamic libraries that can be
configured for the particular scenario. More specifically
we can select what primitive behaviors (e.g. avoid
obstacles, wandering, go forward, etc.), complex tasks
(e.g. robot localization with RFID and vision, detect
removed or abandoned objects, detect people, etc.) and
control algorithms (e.g. event detection, task sequencing,
human operator interaction, etc.) have to start.
To obtain this reconfigurable scheme a key role is played
by the sensory data management sub-system. Each of the
three main components, i.e. controller, executor, and
supervisor, is connected with the sensory input. This
information is used in different ways: at the highest level,
sensory data are converted into events, which are used to
control task executions; at the middle level, sensory data
are used to monitor and control the execution of the task in
progress; finally, at the lowest level, sensory inputs are
used by active behaviors to perform the associated actions.
Surveillance Tasks: Object and People Detection
In this section, specific surveillance tasks are described.
The main purpose of these tasks is to obtain information
about environment changes in a predetermined area. In
particular, we have developed two different classes of
tasks, using a multisensor approach. The first one
monitors the position of predefined objects or the
presence of new ones, whereas the second one detects the
presence of intruders reacting with predefined actions
(e.g. following the person).
Discussion and Conclusion
In this paper, we presented the implementation and
integration of several autonomous navigation and
surveillance functions on a multisensor mobile robot for
robotic site monitoring tasks.
The major aim of the paper was that of providing a
comprehensive overview of the system, as well as
experimental results in real contexts, in order to show the
feasibility of the proposed methods in real-world
situations.
First, we described the architecture of the system based
on a three-layer scheme that allows for modularity and
flexibility, and may supervise a number of basic
navigation tasks and specific surveillance tasks. The
control system makes the robot able to execute
autonomously multiple heterogeneous task sequences in
dynamic environments, since it models the sequential
constraints of the tasks, defines the priority among tasks
and dynamically selects the most appropriate behaviors
in any given circumstance.