OBSTACLE DETECTION AND COLLISION AVOIDANCE USING ULTRASONIC DISTANCE SENSORS FOR AN AUTONOMOUS
QUADROCOPTER
CONCEPT OF OBSTACLE DETECTION AND COLLISION AVOIDANCE
The approach is divided into two main modules: One for Obstacle Detection and one for Collision
Avoidance. The modules are implemented independently of each other. Hence the concept is still
valid and applicable in case of changing or adding sensors of a different kind.
Figure 2 shows the overall concept of the subsystem part, which is presented by this paper. The
ultrasonic raw data is filtered and fused altogether and with IMU (inertial measurement unit) data, before it is proceed to the obstacle detection module. The collision avoidance module uses the results of obstacle detection and enables a controlled flight. Remote data from a computer or an RC (Radio Control) controller for activating and deactivating the system as well as sending steering commands are feed through.
CONCLUSION AND PERSPECTIVE
The evaluation shows, that the system is operational and capable to avoid obstacles and enables
autonomous functions like collision avoidance and position hold and change. Still, the system lacks of some drawbacks since the ultrasonic sensors only measured distances up to about 250cm reliably, Farer distances and problematic surfaces are not detected at all or with the necessary reliability. Improving the quality of the ultrasonic sensors and fusing these sensors with other systems like infrared is needed to improve the system. Since ultrasonic sensors fail to detect all surfaces, other sensors are mandatory. Nevertheless the experiment has shown that ultrasonic sensors are useful in smoky environments and that autonomous flight using only ultrasonic sensors is possible under certain circumstances. Though these positive final results, the distribution of the sensors is not optimal, since the angle of the sensors to the surface of the obstacle has to be within 20°. Arranging all sensors in a circle form; this is not always possible depending on the obstacle. Therefore a distribution with the sensors at the end
of the arms and with higher angle between each sensor should be more effective, which needs to be investigated.