the study and use of optimal control & planning techniques applied to nonlinear dynamic systems (also valid for linear systems), both stable and unstable.
Cell-Mapping techniques combined with reinforcement learning methods. There are many examples of this kind of systems, such as aircrafts, Remotely Piloted Aircrafts Systems (RPAS), satellites, segways, etc.
The technology developed by SOTICOL Robotics Systems has the following remarkable features:
The mathematical model of the controlled system is not necessary
Our technology learns from the experience
is generated from the specific state variables and control actions
linear, non-linear, stable and unstable systems
Independence of the sample period
Optimal control is always applied for each state
thus it obtains a minimization of the error in planning
Reduced maintainability costs
because it is an optimal control
Reduced internal parameters
Capacity of adaptability to the platform
SOTICOL Robotics Systems
The main goal of SOTICOL Robotics Systems is to attend the current demand on technologies applied to RPAS & robots.