Dynamic Gait Adaptation in fixed configuration for Modular Self-Reconfigurable Robots using Fuzzy Logic Control
Advisor Information
Prithviraj Dasgupta
Location
Milo Bail Student Center Omaha Room
Presentation Type
Oral Presentation
Start Date
8-3-2013 9:30 AM
End Date
8-3-2013 9:45 AM
Abstract
Modular self-reconfigurable robots (MSRs) are robots that can dynamically adapt their shape and locomotion. They are very useful for maneuvering in tight spaces or when the task being performed by the robots requires them to change their shape autonomously. MSRs are useful in regions that are difficult for humans to maneuver in, such as s in extra-terrestrial environments, inside volcanic craters, etc. MSRs are composed of a set of individual modules that can connect in different ways with each other to form different types of robot or shapes. When an MSR cannot continue its desired motion in its current shape, the conventional approach is to reconfigure the MSR by detaching the modules from their current shape and reattaching them to form a new shape or configuration. Reconfiguration, however, is a costly operation in terms of time and energy required by the MSR and might reduce the battery life of the MSR modules, if performed frequently. In this research, we study the problem of how an MSR can continue its motion without reconfiguring its modules, but, instead, by adjusting the way or gait with which the modules move. We have proposed a technique from the field of artificial intelligence, called fuzzy logic, for dynamically adapting the gait of MSR modules. Our proposed technique has several advantages – it is straight forward to design, easy to implement, and robust in operation. We have demonstrated the operation of our proposed technique through accurate computer simulations on an MSR called ModRED that we are developing.
Dynamic Gait Adaptation in fixed configuration for Modular Self-Reconfigurable Robots using Fuzzy Logic Control
Milo Bail Student Center Omaha Room
Modular self-reconfigurable robots (MSRs) are robots that can dynamically adapt their shape and locomotion. They are very useful for maneuvering in tight spaces or when the task being performed by the robots requires them to change their shape autonomously. MSRs are useful in regions that are difficult for humans to maneuver in, such as s in extra-terrestrial environments, inside volcanic craters, etc. MSRs are composed of a set of individual modules that can connect in different ways with each other to form different types of robot or shapes. When an MSR cannot continue its desired motion in its current shape, the conventional approach is to reconfigure the MSR by detaching the modules from their current shape and reattaching them to form a new shape or configuration. Reconfiguration, however, is a costly operation in terms of time and energy required by the MSR and might reduce the battery life of the MSR modules, if performed frequently. In this research, we study the problem of how an MSR can continue its motion without reconfiguring its modules, but, instead, by adjusting the way or gait with which the modules move. We have proposed a technique from the field of artificial intelligence, called fuzzy logic, for dynamically adapting the gait of MSR modules. Our proposed technique has several advantages – it is straight forward to design, easy to implement, and robust in operation. We have demonstrated the operation of our proposed technique through accurate computer simulations on an MSR called ModRED that we are developing.