Rovis.Mechatronics represents our set of low-level control algorithms for autonomous mobility. The computer vision data provided by Rovis.AI is used in real-time to calculate and execute the motion of the robotic platforms. We use optimization techniques to evaluate driving and flight trajectories required for calculating the optimal control signals for the robots.


RovisLab AMTU (Autonomous Mobile Test Unit) performing path tracking, obstacle avoidance and motion control.

RovisLab drone motion control based on Rovis.Blockchain, Rovis.Vision and Rovis.Mechatronics.