Ad-hoc Wifi

LIDAR-Lite

v2 Sensors

USB Output BEC

Regulator

IRIS Drone

I2C

Raspberry Pi 3

IRIS Battery

USB

(MAVLink protocol)Radio Control

The increased usage of Unmanned Aerial

Vehicles (UAVs) has also brought an

increase in the number of environments that

drones are expected to be able to fly in.

These environments include areas low to

the ground that are likely to be crowded with

a variety of obstacles. Flying a drone in such

an environment is a difficult task, and

crashing a potentially very expensive UAV is

an all too common experience most would

probably like to avoid.

Proposal

System Housing:

The 3D printed sensor and Raspberry Pi housing fits snugly around

the body of the 3DR IRIS. The housing is designed to hold the Pi

under the lid and mount four sensors 90 degrees apart. It was

designed to minimize weight and allow the user easy access to the Pi.

Final Design

Drone Anti-Collision SystemProject Manager: Gabe Louthan

Technical Manager: Bryan Neufeld

Engineering Team: Keiko Fujii, Alex Spivey, Denis Yablonsky

Marketing Team: Keenan O’Hern, Thaddeus Hughson

Advisors: Dr. Robert Harder, Dr. Gary Spivey

Figure 2: SOLIDWORKS Model of the Housing Assembly

Background

Specifications

Figure 1: Garmin LIDAR-Lite V2 Laser

Distance Sensor

Senior Design

Keenan O’Hern, Alex Spivey, Gabe Louthan,

Bryan Neufeld, Keiko Fujii, Denis Yablonsky

Figure 5. Drone Collision Avoidance

PurposeIn order to make crashes less common, an

obstacle detection and avoidance system is

proposed. Using LIDAR-Lite sensors from

Garmin, the system will detect obstacles in

a remote controlled UAV’s path, and then

take control from the user in order to move

the UAV off a potentially perilous path, and

back to a point of known safety. The

purpose of the project is simultaneously to

fulfill a known need in the drone community

and to give Garmin a way to promote the

use of their LIDAR-Lite sensors in a new

market.

We propose a system of LIDAR-Lite sensors

connected to a Raspberry Pi, in a housing

system that could be mounted on a 3DR

IRIS drone. The Pi will be loaded with

software that will control the sensors and

take control of the drone’s flight if an

obstacle is detected, enabling it to avoid a

collision.

The system needs to support an array of

LIDAR-Lite v2 sensors, override the user if

an obstacle is sensed, and avoid the

obstacle. The design needs to weigh less

than 150 grams so that a 3DR IRIS can

support it while in flight. The system’s

software will process data from the sensors,

and make a decision about the current flight

trajectory. It needs to interface with the UAV

flight management system. The design’s

cost needs to be minimized, as hobbyists

are the target audience.

Figure 4: System Diagram

Electronics:

The Raspberry Pi runs software that interfaces with the Pixhawk, the

IRIS’s flight controller, via the MAVLink protocol. The software also

interfaces with the LIDAR-Lite sensors. When a reading is required of

a sensor, the sensor is powered on, and a reading is communicated

via I2C, and then the sensor is shut off. The Pi is powered by the

IRIS’s battery with the assistance of a USB output BEC regulator.

This eliminated the need for an external battery to power the Pi.

Figure 3: SOLIDWORKS Assembly of the System Housing

Collision Avoidance Algorithm:

The collision detection software records GPS

locations where the drone has been. When an

obstacle is detected by the sensors, the

algorithm determines a previous location to go

back to, and then communicates with the flight

controller, taking control of the drone and

sending it back towards a safe location. After

two seconds, control is returned to the user.

Team

Special thanks to Dennis Corey and Bob Lewis of Garmin and

Bruce Cleveland of Bend Poly

Acknowledgements