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Using of Reinforcement Learning for Four Legged Robot Control
Ondroušek, Vít ; Maga,, Dušan (referee) ; Maňas, Pavel (referee) ; Singule, Vladislav (referee) ; Březina, Tomáš (advisor)
The Ph.D. thesis is focused on using the reinforcement learning for four legged robot control. The main aim is to create an adaptive control system of the walking robot, which will be able to plan the walking gait through Q-learning algorithm. This aim is achieved using the design of the complex three layered architecture, which is based on the DEDS paradigm. The small set of elementary reactive behaviors forms the basis of proposed solution. The set of composite control laws is designed using simultaneous activations of these behaviors. Both types of controllers are able to operate on the plain terrain as well as on the rugged one. The model of all possible behaviors, that can be achieved using activations of mentioned controllers, is designed using an appropriate discretization of the continuous state space. This model is used by the Q-learning algorithm for finding the optimal strategies of robot control. The capabilities of the control unit are shown on solving three complex tasks: rotation of the robot, walking of the robot in the straight line and the walking on the inclined plane. These tasks are solved using the spatial dynamic simulations of the four legged robot with three degrees of freedom on each leg. Resulting walking gaits are evaluated using the quantitative standardized indicators. The video files, which show acting of elementary and composite controllers as well as the resulting walking gaits of the robot, are integral part of this thesis.
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Implementaion of the controllers of a mobile walking robot
Krajíček, Lukáš ; Věchet, Stanislav (referee) ; Ondroušek, Vít (advisor)
This diploma thesis deals with design and implementation of the controllers of a mobile walking robot. The advantage of these controllers are their kinematics and geometrics independent representation, which allow to use them for different robot types and tasks. In this thesis the contact controller is designed, which minimizes residual forces and torques at the robot's center of gravity, and thereby stabilize robot's body. Next the thesis deals with a posture controller, which maximizes a heuristic posture measure to optimize posture of robot body. Because of this optimization, legs are moved away from their limits and therefore they have more working space for next move. Implementation of the chosen solution is made on the robot's MATLAB mathematical model. Controllers are composed into a control basis, that allows to solve general control tasks by simultaneous combination of contained controllers. The algorithm was created for that simultaneous activation and its operation was explained on flow charts.
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Utilization of the inertial sensors for control of the mobile robots
Lachnit, Zdeněk ; Ondroušek, Vít (referee) ; Houška, Pavel (advisor)
The main subject of this thesis is use of inertial sensors for better motion and stability control of mobile robots. In background research are described the basic methods of mobile robots localization. Second part of background research is about mobile robot stability, in this part are described the methods of mobile robots stability control. In next part is description of MEMS accelerometers and gyroscopes and description of basic method of filtering and integration which are useful for input processing of these sensors. Thesis continues with inertial sensors analysis for application on control of wheeled and legged mobile robots. In end of thesis are specified the experiment results, which confirm the applicability of sensors for mobile robot control.
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Using of Reinforcement Learning for Four Legged Robot Control
Ondroušek, Vít ; Maga,, Dušan (referee) ; Maňas, Pavel (referee) ; Singule, Vladislav (referee) ; Březina, Tomáš (advisor)
The Ph.D. thesis is focused on using the reinforcement learning for four legged robot control. The main aim is to create an adaptive control system of the walking robot, which will be able to plan the walking gait through Q-learning algorithm. This aim is achieved using the design of the complex three layered architecture, which is based on the DEDS paradigm. The small set of elementary reactive behaviors forms the basis of proposed solution. The set of composite control laws is designed using simultaneous activations of these behaviors. Both types of controllers are able to operate on the plain terrain as well as on the rugged one. The model of all possible behaviors, that can be achieved using activations of mentioned controllers, is designed using an appropriate discretization of the continuous state space. This model is used by the Q-learning algorithm for finding the optimal strategies of robot control. The capabilities of the control unit are shown on solving three complex tasks: rotation of the robot, walking of the robot in the straight line and the walking on the inclined plane. These tasks are solved using the spatial dynamic simulations of the four legged robot with three degrees of freedom on each leg. Resulting walking gaits are evaluated using the quantitative standardized indicators. The video files, which show acting of elementary and composite controllers as well as the resulting walking gaits of the robot, are integral part of this thesis.
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|
|
Using of Reinforcement Learning for Four Legged Robot Control
Ondroušek, Vít ; Březina, Tomáš (advisor)
The Ph.D. thesis is focused on using the reinforcement learning for four legged robot control. The main aim is to create an adaptive control system of the walking robot, which will be able to plan the walking gait through Q-learning algorithm. This aim is achieved using the design of the complex three layered architecture, which is based on the DEDS paradigm. The small set of elementary reactive behaviors forms the basis of proposed solution. The set of composite control laws is designed using simultaneous activations of these behaviors. Both types of controllers are able to operate on the plain terrain as well as on the rugged one. The model of all possible behaviors, that can be achieved using activations of mentioned controllers, is designed using an appropriate discretization of the continuous state space. This model is used by the Q-learning algorithm for finding the optimal strategies of robot control. The capabilities of the control unit are shown on solving three complex tasks: rotation of the robot, walking of the robot in the straight line and the walking on the inclined plane. These tasks are solved using the spatial dynamic simulations of the four legged robot with three degrees of freedom on each leg. Resulting walking gaits are evaluated using the quantitative standardized indicators. The video files, which show acting of elementary and composite controllers as well as the resulting walking gaits of the robot, are integral part of this thesis.
|
|
|
Implementaion of the controllers of a mobile walking robot
Krajíček, Lukáš ; Věchet, Stanislav (referee) ; Ondroušek, Vít (advisor)
This diploma thesis deals with design and implementation of the controllers of a mobile walking robot. The advantage of these controllers are their kinematics and geometrics independent representation, which allow to use them for different robot types and tasks. In this thesis the contact controller is designed, which minimizes residual forces and torques at the robot's center of gravity, and thereby stabilize robot's body. Next the thesis deals with a posture controller, which maximizes a heuristic posture measure to optimize posture of robot body. Because of this optimization, legs are moved away from their limits and therefore they have more working space for next move. Implementation of the chosen solution is made on the robot's MATLAB mathematical model. Controllers are composed into a control basis, that allows to solve general control tasks by simultaneous combination of contained controllers. The algorithm was created for that simultaneous activation and its operation was explained on flow charts.
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|
|
Utilization of the inertial sensors for control of the mobile robots
Lachnit, Zdeněk ; Ondroušek, Vít (referee) ; Houška, Pavel (advisor)
The main subject of this thesis is use of inertial sensors for better motion and stability control of mobile robots. In background research are described the basic methods of mobile robots localization. Second part of background research is about mobile robot stability, in this part are described the methods of mobile robots stability control. In next part is description of MEMS accelerometers and gyroscopes and description of basic method of filtering and integration which are useful for input processing of these sensors. Thesis continues with inertial sensors analysis for application on control of wheeled and legged mobile robots. In end of thesis are specified the experiment results, which confirm the applicability of sensors for mobile robot control.
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