Contributions to Proceedings:

D. Naydenov, M. Bader:
"Position tracking of a model race car with Inertial Measurement Unit, laser mouse sensor and Extended Kalman Filter";
in: "Proceedings of the 25th International Conference on Robotics in Alpe-Adria-Danube Region (RAAD)", Springer, 2016, 8 pages.

English abstract:
Autonomous navigation (path-planning, self-localisation and
mapping) has become important for the scientific community due to the
increasing interest in self-driving vehicles. This work presents a position
tracking system without wheel or motor encoders. The system relies on
combining data from the input throttle and steering angle (motion com-
mands) with measurements from an Inertial Measurement Unit (IMU)
and a laser mouse sensor, using an Extended Kalman Filter (EKF) as
a correction mechanism. The system is able to track the vehicle pose
at a rate of 100Hz, allowing an accurate position estimate between the
self-localisation cycles, which are typically working at a rate of 5-20Hz.
The approach has been implemented and evaluated, achieving position
accuracy of 97% for distances up to 10m on a flat surface.

robotic control car planning

Created from the Publication Database of the Vienna University of Technology.