seminar code
04-08-2014, 11:17 AM
Automatic Docking System for Recharging Home Surveillance Robots
[attachment=66539]
Abstract
This paper presents the development and
characterization of a surveillance robot with automatic
docking and recharging capabilities for home security. The
proposed system is composed of a surveillance robot and a
docking station. The palm-sized surveillance robot has a
triangular shape with three wheels. It communicates with the
general wireless home router through WiFi. It communicates
with the docking station through ZigBee and serves as a
mobile wireless sensor network gateway. The docking station
has a trapezoidal structure with an arc-shaped docking
interface. A docking method based on the self-localization of
the robot and the infrared detectors of the docking station is
proposed. The robot can return to the docking station for
recharging operations when the on-board battery is too low.
The experimental results show that the prototype robot
achieved a success rate of 90% after 60 different docking
attempts
INTRODUCTION
With the rapid development of microelectronics and
wireless communication technologies, mobile robots are being
widely used in industrial automation, home automation,
hospitals, entertainment, space exploration, military, etc [1]. In
recent years, as the size and the cost of mobile robots have
decreased significantly, they are finding increasing uses in
home environments. More and more mobile robots are now
working around us and they will help us a lot in our daily lives
[2] [3]. Various home robots have been proposed to do
housework such as cooking, cleaning, house plant watering,
pet feeding and taking care of children [4] [5].
Home security is one of the typical applications of home
robots. In traditional home security systems, monitoring
devices are usually mounted on fixed locations such as doors,
windows and walls. A home surveillance system based on an
embedded system with multiple ultrasonic sensor modules has
been presented in [6]. If any intruder passes through the
ultrasonic sensing area, the ultrasonic transmission will be
blocked by the human body. The authors use a Majority
Voting Mechanism (MVM) to process the output signals from
multiple ultrasonic receivers. An automatic video-based
SYSTEM DESIGN
The conceptual architecture of a home security system
based on the proposed surveillance robot and the docking
station is shown is Fig. 1. The surveillance robot can work in
three modes according to user requests and task properties:
patrolling mode, first responder mode and remote control
mode. In the patrolling mode, the surveillance robot wanders
around in the rooms or follows predefined routes
autonomously. When security related information is acquired,
it will be sent to the home server for further analysis. In the
first responder mode, the surveillance robot is programmed to
work in cooperation with other fixed monitoring devices.
When one of those devices reports a security event to the
surveillance robot, it will navigate to the target region to
The Surveillance Robot
The hardware architecture of the surveillance robot is
shown in Fig. 3. The two DC motors provide power for
rotating the two rear wheels. The servo is used for tilting the
camera for a wide field of view. The voltage detection module
is mainly used for real-time detection of the battery status. In
the normal working status, when detecting that the battery
voltage is lower than the preset charging voltage, the core
board will command the robot to return to the docking station
for recharging. In the charging status, when detecting that the
battery voltage is higher than the preset working voltage, the
core board will command the robot to start to work again.
DOCKING METHOD
If the surveillance robot wants to recharge by itself
whenever the battery voltage is low, it must be able to
navigate back to the docking area and connect with the
docking station automatically. Some key techniques include
self-localization, global and local path planning, docking and
charging status detection, and fault-tolerant processing. Before
reaching the docking area, the robot mainly depends on its
own locomotion capabilities to work. In the final docking
process, the robot and the docking station work cooperatively
to complete the task.
EXPERIMENTAL RESULTS
A testbed has been built in our laboratory for the
automatic docking experiments. The testbed setup is shown
in Fig. 13. A laptop computer runs the high-level control
programs and provides the graphic user interface. Through
the graphic user interface, a user can remote control thesurveillance robot and watch the real-time video transmitted
back by the surveillance robot. Both the laptop computer and
the surveillance robot connect to a wireless local area
network router through WiFi. The surveillance robot
communicates with the docking station through ZigBee.
Some experiments have been devised and performed to
evaluate the locomotion performance and the automatic
docking performance of the implemented surveillance robot.
In the path planning of the surveillance robot, we use only
two basic motion components, i.e. going-straight and
in-situ turning. We have performed calibration experiments
to increase the accuracy of self-localization and navigation.
CONCLUSION
We have presented the design and implementation of a
surveillance robot with automatic docking and recharging
capabilities for home security. A docking method based on the
self-localization of the robot and the infrared detectors of the
docking station is proposed. The robot can navigate back to the
docking station for recharging operations when the on-board
battery is too low. The prototype robot achieved a success rate of
90% after 60 different docking attempts.
Future work will focus on improving the current prototype robot
to enable more functions. We plan to address several technical
challenges such as visual navigation, adding more docking stations,
and the automatic battery replacement mechanism
[attachment=66539]
Abstract
This paper presents the development and
characterization of a surveillance robot with automatic
docking and recharging capabilities for home security. The
proposed system is composed of a surveillance robot and a
docking station. The palm-sized surveillance robot has a
triangular shape with three wheels. It communicates with the
general wireless home router through WiFi. It communicates
with the docking station through ZigBee and serves as a
mobile wireless sensor network gateway. The docking station
has a trapezoidal structure with an arc-shaped docking
interface. A docking method based on the self-localization of
the robot and the infrared detectors of the docking station is
proposed. The robot can return to the docking station for
recharging operations when the on-board battery is too low.
The experimental results show that the prototype robot
achieved a success rate of 90% after 60 different docking
attempts
INTRODUCTION
With the rapid development of microelectronics and
wireless communication technologies, mobile robots are being
widely used in industrial automation, home automation,
hospitals, entertainment, space exploration, military, etc [1]. In
recent years, as the size and the cost of mobile robots have
decreased significantly, they are finding increasing uses in
home environments. More and more mobile robots are now
working around us and they will help us a lot in our daily lives
[2] [3]. Various home robots have been proposed to do
housework such as cooking, cleaning, house plant watering,
pet feeding and taking care of children [4] [5].
Home security is one of the typical applications of home
robots. In traditional home security systems, monitoring
devices are usually mounted on fixed locations such as doors,
windows and walls. A home surveillance system based on an
embedded system with multiple ultrasonic sensor modules has
been presented in [6]. If any intruder passes through the
ultrasonic sensing area, the ultrasonic transmission will be
blocked by the human body. The authors use a Majority
Voting Mechanism (MVM) to process the output signals from
multiple ultrasonic receivers. An automatic video-based
SYSTEM DESIGN
The conceptual architecture of a home security system
based on the proposed surveillance robot and the docking
station is shown is Fig. 1. The surveillance robot can work in
three modes according to user requests and task properties:
patrolling mode, first responder mode and remote control
mode. In the patrolling mode, the surveillance robot wanders
around in the rooms or follows predefined routes
autonomously. When security related information is acquired,
it will be sent to the home server for further analysis. In the
first responder mode, the surveillance robot is programmed to
work in cooperation with other fixed monitoring devices.
When one of those devices reports a security event to the
surveillance robot, it will navigate to the target region to
The Surveillance Robot
The hardware architecture of the surveillance robot is
shown in Fig. 3. The two DC motors provide power for
rotating the two rear wheels. The servo is used for tilting the
camera for a wide field of view. The voltage detection module
is mainly used for real-time detection of the battery status. In
the normal working status, when detecting that the battery
voltage is lower than the preset charging voltage, the core
board will command the robot to return to the docking station
for recharging. In the charging status, when detecting that the
battery voltage is higher than the preset working voltage, the
core board will command the robot to start to work again.
DOCKING METHOD
If the surveillance robot wants to recharge by itself
whenever the battery voltage is low, it must be able to
navigate back to the docking area and connect with the
docking station automatically. Some key techniques include
self-localization, global and local path planning, docking and
charging status detection, and fault-tolerant processing. Before
reaching the docking area, the robot mainly depends on its
own locomotion capabilities to work. In the final docking
process, the robot and the docking station work cooperatively
to complete the task.
EXPERIMENTAL RESULTS
A testbed has been built in our laboratory for the
automatic docking experiments. The testbed setup is shown
in Fig. 13. A laptop computer runs the high-level control
programs and provides the graphic user interface. Through
the graphic user interface, a user can remote control thesurveillance robot and watch the real-time video transmitted
back by the surveillance robot. Both the laptop computer and
the surveillance robot connect to a wireless local area
network router through WiFi. The surveillance robot
communicates with the docking station through ZigBee.
Some experiments have been devised and performed to
evaluate the locomotion performance and the automatic
docking performance of the implemented surveillance robot.
In the path planning of the surveillance robot, we use only
two basic motion components, i.e. going-straight and
in-situ turning. We have performed calibration experiments
to increase the accuracy of self-localization and navigation.
CONCLUSION
We have presented the design and implementation of a
surveillance robot with automatic docking and recharging
capabilities for home security. A docking method based on the
self-localization of the robot and the infrared detectors of the
docking station is proposed. The robot can navigate back to the
docking station for recharging operations when the on-board
battery is too low. The prototype robot achieved a success rate of
90% after 60 different docking attempts.
Future work will focus on improving the current prototype robot
to enable more functions. We plan to address several technical
challenges such as visual navigation, adding more docking stations,
and the automatic battery replacement mechanism