The commercial use of drones will revolutionize numerous applications, from package delivery to infrastructure inspection, mapping, and more. But large scale operations, especially in urban areas, depend on getting access to shared airspace and providing autonomous, safe operations anytime and anywhere.
Safety is this market’s enabler and in the heart of the rapidly developing drone regulation that is strongly promoted by the biggest industry players (such as Amazon, Google, Airbus, and more) and includes broad situational awareness requirements for navigation, obstacle detection and avoidance, and safe emergency landings.
Wonder Robotics realized that a drone’s complex and diversified vision requirements cannot be satisfied by 2D or 3D vision capture alone. Our computer vision technology is modeled after and inspired by a human vision-based replica. This replica uniquely transcends prior art by combining short-range 3D depth perception with a long-range 2D vision for dramatically improved perspective, classification, shading, texture, and motion cues.
Our goal is to become a leading provider of intelligent and robust AI layers for autonomous and safe flights for both commercial and military drones by utilizing highly advanced vision-based capabilities.
WonderLand is a highly unique solution that allows vertical take-off and landing (VTOL) drones to land safely and completely autonomously on any uncharted, unprepared, and unattended site, without operator involvement or supervision of any kind.
WonderLand is a self-contained airborne POD with complete onboard autonomy and does not depend on any external communication or GPS reception.
In simplistic terms, WonderLand combines advanced 2D semantic algorithms to determine an approximate landing area based on various factors (including flight altitude).
Using a 3D sensor and proprietary algorithms, it performs a highly complex geometric analysis to verify that the landing site is clear of obstacles, slopes, cables, and other encumbrances, both static and mobile. The drone is then safely and autonomously brought to a perfect precision landing while ensuring that no risk is imposed on nearby objects (e.g., human beings).
We are developing cutting-edge technologies that will facilitate the drone revolution taking into consideration the completely new regulation that will emerge.
The WonderLand system provides any drone with the capability to land completely autonomously by detecting structures, low and high profile obstacles, and even human activity below the Platform. This is done using computer sensing and machine learning algorithms and by guiding the drone through a clear path to a safe landing.
Wonderland enables an accurate landing. In fact, it enables drones to land within a few centimeters’ accuracy.
A drone equipped with Wonderland will be able to land on charging stations or Drone Mail Boxes quickly and accurately, even if the box was not in the drone’s database before take-off.
Wonderland can be deployed in situations when the drone needs to verify that the ground or the path to the ground is free from obstacles, such as drone delivery. Wonderland is highly effective for clearing the delivery zone for cable-based delivery drones, package dropping, and even when a drone needs to land on the ground to deliver the package.
WonderLand can be used when GPS signal is lost. A drone equipped with our product will be able to safely hover in place without GPS and will not drift away even in strong winds.
Once GPS signal is restored, the drone will be able to continue its mission. Additionally, the operator will be able to navigate to the landing area if he can visually orientate himself or decide to command the WonderLand to safely land the drone.
One way or another, risks to the drone, its surroundings, and people on the ground are completely mitigated.
In its roadmap, Wonder Robotics will focus on a new generation of autonomous and advanced piloting assistance systems that will enable drones to rely on a variety of sensors to create an accurate 3D perception of the environment.
Measuring distance and creating a 3D model of the environment represents a necessary component for machine vision systems to comprehend the scene.
That comprehension, combined with a convolutional neural network, enables the system to identify objects and their respective distances and make the most appropriate decisions for the situation, in conjunction with other sensor modalities.
The company’s birth resulted from the founders delivering a unique drone solution to a customer in their previous workplace. The drone was carrying a heavy payload with limited endurance. The end-user asked for the drone to have a safe, autonomous landing on the target area to allow for extended operations time. While they were looking for such a solution, the founders realized that not only did such a solution not exist but that once developed, such technology had virtually unlimited potential to be sold across a broad spectrum of industries. The founders then took a leap of faith, and Wonder Robotics was launched shortly thereafter.
Innovator & entrepreneur with 20 years in business leadership in the domains of drones & HLS.
Experienced VP Sales and Business Development in Commercial Drone application, software products, 3D mapping and Aerospace industry.
An experienced expert in real-time embedded systems as well as computer-vision, image algorithms and processing.
Mr. Shimon started flying radio control models in his childhood. He was the Israeli RC aerobatics model champion in 1995 and served as a UAV operator in the Israeli Intelligence Corps. Afterward, Mr. Shimon was among the founders of a leading UAV company – Aeronautics Ltd and served as a Senior VP Marketing for over 12 years until the company grew to more than 700 employees. Mr. Shimon has an LLB degree from the TAU.
Mr. Shimon has 20 years of experience in international sales & marketing in the defense & homeland security markets, in addition to a proven record of success in sales, sales management, governmental contracting, and business development. Mr. Shimon has conducted multi-million-dollar transactions worldwide and has strong technical skills in addition to a deep know-how of diversified technologies in the drones, sensors, and interception domains.
As an entrepreneur, Mr. Shimon is an Angel Investor and a director in several successful startup companies across a broad spectrum of industries and disciplines.
Given his experience, Mr. Shimon is a recognized authority in unmanned systems with vast experience in all commercial, operation, and technology aspects of drones and their ancillary subsystems, and enjoys a wide local and international network in the drone tech and aerospace industry.
Yonatan Sade, born in 1985, holds a B.Sc. degree from Jerusalem College of Technology (JCT) and an M.Sc. degree from Tel-Aviv University (TAU), both in electrical engineering. The master’s degree focused on image processing and computer vision.
During his B.Sc. studies, he worked as a student at Intel in a group of design & validation of network interface controller cards (NICs) for clients and servers.
After his studies, Yonatan worked in ENGS Systems for 4 years where he was exposed to the real-time embedded systems world design and implementation, including micro-controllers, hard and soft real-time C programming for embedded systems, and design-to-production concepts. Then, Yonatan worked for more than 4 years as a team leader of the SW team in Netzer Precision Position Sensors, a leading global company producing rotary encoders, and played a central and important role in developing and designing the new and revolutionary products of the company, including all the aspects of product manufacturing. i.e., High- and low-level software programming, analog and digital hardware design, and mechanics aspects from the customer’s side.
Professionally, Yonatan gained substantial experience in real-time embedded systems world design and implementation, including micro-controllers, hard and soft real-time C programming for embedded systems, and design-to-production concepts. Yonatan has experience in microcontrollers, ARM cortex, communication protocols, C, C++, C#, OpenCV, VHDL, FPGAs, analog design, signal processing, and MATLAB.