| dc.description.abstract | Robotic vehicles are normally modeled as rigid bodies under general motion,
combining translation and rotation motions. While such modeling results in motion
controllers that are easy to implement, these controllers are also limited in the number of
degrees of freedom (DOF) that can be controlled. The robotic vehicle with limited DOF
operates well in structured terrain conditions with sufficient stability and friction. When the
vehicle is operated in unstructured terrains, such as those that are sandy, snowy, or steep
terrains, which might be slippery, such an approach fails to operate well. Since additional
applications of robotic vehicles are in unstructured terrains, it is important to find
alternative control models that will increase the number of controllable DOF and add more
robustness and flexibility to the vehicle's performance.
This thesis proposes the modeling of a vehicle as a system of particles centered at
the wheels, with each particle controlled independent of one another in order to achieve the
desired vehicle motion. In this work, the Particle Model Control approach was tested on the
robotic platform BIBOT-1. The work illustrated the major vehicle kinematics under
different steering modes and how the controls for the robotic motion can be formulated on
the basis of Particle Modeling. A control system, based on Particle Modeling using
decentralized control architecture, was designed and tested on BIBOT-1. The preliminary
test results obtained from the trial runs were then analyzed on the basis of root mean square
(R.M.S.) error performance factors. Some future work was also suggested in order to gather
more results and validate the modeling approach. | en_US |
