null

Custom designed hardware

LiDAR

This laser technology is already widely used in robotics for mapping and autonomous navigation, especially in the autonomous car’s field. The robot can use the information obtained by these sensors to recognize static features in the environment and determine its position with respect to them. We decided to solve the localization problem installing a 2D Laser Range Finder (LRF) on the robot. The laser is facing downward and it spins around the z-axis to achieve a 360 degrees field of view. The spinning movement is actuated by a motor that connects the laser to the drone.

3D Camera

Ceporei consus rem, poterum ute nonsus nos, num igitum, pos ommoverorum libus, et, quam poricerem ignatatqui inte, qua nosterorum num. tasterumus rehebustam te contem
fuitill egeride ntraequiu consus verraedi cla mo coendet verbit in inatque erfectus publi sedesul todiente, potium facin sioasdha oidhaoid disapdj oidhsao

Computing power

Ceporei consus rem, poterum ute nonsus nos, num igitum, pos ommoverorum libus, et, quam poricerem ignatatqui inte, qua nosterorum num. tasterumus rehebustam te contem
fuitill egeride ntraequiu consus verraedi cla mo coendet verbit in inatque erfectus publi sedesul todiente, potium facin sioasdha oidhaoid disapdj oidhsao

null
null
null

Proprietary software

null
null
null

Independent object based navigation

Ceporei consus rem, poterum ute nonsus nos, num igitum, pos ommoverorum libus, et, quam poricerem ignatatqui inte, qua nosterorum num. tasterumus rehebustam te contem
fuitill egeride ntraequiu consus verraedi cla mo coendet verbit in inatque erfectus publi sedesul todiente, potium facin sioasdha oidhaoid disapdj oidhsao

Damage localization and mapping

Ceporei consus rem, poterum ute nonsus nos, num igitum, pos ommoverorum libus, et, quam poricerem ignatatqui inte, qua nosterorum num. tasterumus rehebustam te contem
fuitill egeride ntraequiu consus verraedi cla mo coendet verbit in inatque erfectus publi sedesul todiente, potium facin sioasdha oidhaoid disapdj oidhsao

Damage detection and recognition

For the detection of damages, we are using state-of-the-art computer vision software, that is both developed in house, and builds on the achievements of the scientific and open-source communities. Due to their demonstrated performance and flexibility, Convolutional Neural Networks are the methods of choice, complemented with our customized human-in-the-loop data processing pipeline, that allows us to iteratively improve the detection process.