THESIS
2017
xiii, 79 pages : illustrations ; 30 cm
Abstract
To meet the demand of short-distance transportation, a novel type of intelligent
mobility robot is proposed by this thesis. The robot features high portability, reliable
safety and multiple control and interaction methods, including posture control and
remote interaction. The robot has wide range of application prospects in both
industrial production and daily life, such as travel, services, entertainment, etc.
To realize posture control of the robot, a complete set of posture perception
system is designed and developed. Firstly, the pressures on different sections are real-time
acquired by specific sensors and corresponding detection circuit. Then based on
the pressure distributions and statistic information, the posture is perceived by a
series of processing algorithms, inclu...[
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To meet the demand of short-distance transportation, a novel type of intelligent
mobility robot is proposed by this thesis. The robot features high portability, reliable
safety and multiple control and interaction methods, including posture control and
remote interaction. The robot has wide range of application prospects in both
industrial production and daily life, such as travel, services, entertainment, etc.
To realize posture control of the robot, a complete set of posture perception
system is designed and developed. Firstly, the pressures on different sections are real-time
acquired by specific sensors and corresponding detection circuit. Then based on
the pressure distributions and statistic information, the posture is perceived by a
series of processing algorithms, including sampling a reference posture when the user
is standing stably and calculating current user posture by an non-linear mapping.
Next, the posture is quantitatively described as the inclination angles of the body
gravity center in two dimensions. Moreover, two machine learning are applied to
further improve the accuracy of posture detection, including parameter regression
method and Gaussian Process Dynamic Model. In addition, some auxiliary sensors
are also applied to ensure the robustness and reliability through fusion of multi-sensor
information. At last, with the help of hybrid neural network, some interaction
via posture patterns are achieved.
This thesis also analyzes the planar kinematics of the intelligent mobility robot, considering its steering mechanisms, suspension systems, and differential speed of
wheel pairs. The motion planning algorithm outputs desired motion parameters of
the robot, such as longitudinal speed and turning curvature, based on both user input
and kinematic constrains. To control the motion of the robot, the distribute control
strategy as well as fuzzy logic control algorithm are applied to coordinately assign
appropriate control amount to multiple actuators of different types.
The design and control methods of actuators are discussed at last. This thesis
designs and implements the Field Oriented Control to drive the Permanent Magnet
Synchronous Motor and to control its speed and toque. The FOC system improves
energy efficiency and decreases the operation noise and toque ripple. Meanwhile, a
kind of brake device is also designed by the thesis to provide reliable and timely
braking performance, wherein the braking force is adjustable.
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