To kick things off for our seminar series, we are starting with a graduate student double header this Friday. Elisha Pruner will give a talk on “Formation control of multi-robot teams using geometric and self-organizing approaches” and Mostafa Mohammed will talk about “Application of Mechatronics in Individual Drive Electric Motors for Unmanned Off-road Wheeled Vehicles”.
The seminar abstracts are below
Date: Friday 11th January
Room: SITE G0103
Hope to see you all there!
Formation control of multi-robot teams using geometric and self-organizing approaches
In certain applications, such as search and rescue, reconnaissance, and surveillance, many small inexpensive vehicles working as a team can achieve more than one sophisticated vehicle working on its own. Currently, there is a strong motivation to implement multi-vehicle teams since they can perform tasks with greater efficiency, less cost, and they present a more robust solution. However, the disadvantage of multi-vehicle systems is that they require a high level of organization and coordination in order to successfully complete a task. Formation control is a field of engineering that addresses this issue, and provides coordination schemes to successfully implement multi-vehicle systems. In this research two types of formation controllers were developed: geometric and self-organizing. Firstly, a geometric formation controller was created using a leader-follower setup and a PD controller, generating military style formations for the robot teams such as platoon and V-formation. Furthermore, a self-organizing controller was developed using a velocity-potential approach to create swarming movements for the robot team with no pre-defined shape. Both geometric and self-organizing formation controllers were first prototyped in MATLAB simulation; they were then programmed onto three differential drive mobile robot platforms for experimental testing. The results confirmed the validity of both formation control approaches.
Application of Mechatronics in Individual Drive Electric Motors for Unmanned Off-road Wheeled Vehicles
Under the supervision of Dr. Dan S. Necsulescu
Energy consumption optimization is applied to a mobile robot to benefit from the kinetic energy gained along downhill slopes, in the off-road environment, to overcome the uphill slopes. Predictive control is used, assuming that the robot knows the environment map ahead of time before reaching a ditch. The energy consumed as well as the motors’ speed profiles during the operation are investigated. The simulation results obtained are compared to those of a PID speed controller and to those of an open-loop control of the DC motors. The results obtained with predictive controller showed a noticeable reduction in the energy consumption over the PID controller and the open-loop control which failed to overcome the ditch. An experimental work was conducted using wood made ramps to represent the ditch in a laboratory environment. A mobile robot is required to attempt crossing the ditch. The experimental results showed good agreement with the simulation results for open-loop, PID and predictive controllers. Predictive controller proved the most efficient solution.