RelaSyS -
Drone Reliability Assessment Solution

Reliable Autonomous Systems

Relasys

About us

Who

RELASYS is EPFL based startup intended to facilitate the procedure for evaluating the performance of the drone’s on-board Sense-and-Avoid (S&A) system. RELASYS provides the private and academic clients with tailor-made integrated test facility to evaluate the performance of onboard S&A for small drones.


Problem

Postal and delivery companies are pursuing large-scale autonomous Unmanned Aerial Vehicle (UAV) fleet as a future of point-to-point delivery system. This interesting application requires reliable mechanism to keep predefined safe distance from the ground and other obstacles. In addition to a separation assurance, a mechanism to collaborative keep minimum separation distance between aircrafts, on-board S&A is considered as a last resort manoeuver to present a collision in case of loss of separation. The detection of non-broadcasting conflicting objects in the vicinity of the UAV needs to performed by the onboard sensing and avoiding system.  

Solution

RelaSyS, short for Reliable Autonomous Systems, makes people be & feel safe as they benefit from autonomous drones. At RelaSyS, we help drone manufacturers & civil aviation authorities for "safe and reliable" integration of drones in our daily life. We provides solutions for systematic evaluation of the reliability of on-board sense & avoid (S&A) systems in avoiding collisions with people, other drones and urban obstacles in variety of collision conditions. The results of our in-depth study determines in which conditions the autonomous drones could be authorized to operate without any considerable risk of collision. 

Illustrative Example

Four collision scenarios are demonstrated in this illustrative example. An intruder drone, on the left, collides with a test drone. The test drone's S&A feature is disabled. 

Meet the Team

Dr. Ali Motamed

Co-founder of RelaASyS, has hands-on knowledge on design, fabrication, analysis and optimization of the mechatronic systems. Graduated from EPFL, Lausanne, he has been involved as project manager and scientist in many applied research projects in collaboration with academic and industrial partners.   

Hanif Tabatabaee

EPFL graduate, Hanif has eight year of experience as senior manager in product management in a multi-national company. He has lead a product development for a never-explored market.

Dr. Sina Mirrazavi Salehian

Seyed Sina Mirrazavi Salehian is a Postdoctoral researcher at the Learning Algorithms and Systems Laboratory (LASA) at the Swiss Federal Institute of Technology in Lausanne (EPFL). He has recently received his Ph.D. in Robotics from the same institute. His research interests focus on robot control, obstacle avoidance multi-robot interaction.

Dr. Mehran Khaghani

PhD in robotics, control, and intelligent systems from EPFL. Researcher in aerial robotics and navigation. Developed a patented navigation algorithm for UAVs. Experience in oil and gas industry as head of engineering team and scientific advisor.

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