Omnidirectional visual obstacle detection using embedded FPGA

For autonomous navigation of Micro Aerial Vehicles (MAVs) in cluttered environments, it is essential to detect potential obstacles not only in the direction of flight but in their entire local environment. While there exist systems that do vision based obstacle detection, most of them are limited to a single perception direction. Extending these systems to a multi-directional sensing approach would exhaust the payload limit in terms of weight and computational power. We present a novel light-weight sensor setup comprising of four stereo heads and an inertial measurement unit (IMU) to perform FPGA-based dense reconstruction for obstacle detection in all directions. As the data-rate scales up with the number of cameras we use an FPGA to perform streaming based tasks in real-time and show a light-weight polar-coordinate map to allow a companion computer to fully process the data of all the cameras and perform obstacle detection in real-time. The system is able to process up to 80 frames per second (fps) freely distributed on the four stereo heads while maintaining a low power budget. The perception system including FPGA, image sensors and stereo mounts is 235 g in weight.

Authors

• Pascal Gohl
• Dominik Honegger
• Sammy Omari
• Markus W. Achtelik
• Marc Pollefeys
• Roland Siegwart

Keywords

• Robot sensing systems
• Cameras
• Collision avoidance
• Three-dimensional displays
• Field programmable gate arrays
• Head
• Obstacle Avoidance
• Power Calculation
• Aerial Vehicles
• Image Sensor
• Inertial Measurement Unit
• Single Direction
• Flight Direction
• Micro Air Vehicles
• Cluttered Environments
• Imaging Data
• Low Resolution
• Path Planning
• Local Map
• Mapping Resolution
• 3D Point
• Map Representation
• Camera Frame
• Update Rate
• Stereo Images
• Disparity Map
• Disparate Data
• Stereo Matching
• Stereo Camera
• Stereo Pairs
• Outlier Rejection
• Flight Test
• Distance Sensor
• Dynamic Scenes
• Camera System