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Job description

In this role, the employee will work to develop a suite of technology features applied to Light Electric Vehicles (like eBikes and electric scooters) so as to improve the  situational awareness of the operator.

Desired majors: computer science, computer engineering, electrical engineering, Systems engineering, Robotics.

*Required: * 1)

Deep experience in embedded software (firmware) development. 

2) Appreciation of startup company mentality- we are on the ground floor of potentially disruptive technology.  We often work long hours at below-market rate with the intentions of future gains. Note that as a startup, we currently do not offer any benefits.

Desired Skills include: embedded software coding, C++, machine learning, control systems, sensors, robotics, data science

All work will take place at our office on the campus of Lawrence Tech University in Southfield, MI. Specifically, our lab and office are located here{rel="noopener noreferrer"}. 

40 hours per week is allocated for this position.  Working hours are flexible.  This is a long-term position.

Company

GEKOT Robotics's ML-based tech solutions enable e-scooter rental fleet operators to reduce accidents and comply with safety technology mandated by cities. GEKOT Robotics utilizes IoT, sensors, and alerts for sidewalk detection and collision avoidance. 

www.gekotinc.com{rel="noopener noreferrer"}

Background

Almost all vehicle accidents are caused by human error.  Modern automobile mitigate such accidents by way of applied situational awareness technology such as:

• Pedestrian detection
• Hazard avoidance
• Lane departure warning/correction
• Blind spot detection

These complex solutions relay on a costly suite of technology which makes them unfeasible for Light Electric Vehicles such as:

• e-bikes
• electric scooters
• mobility scooters
• golf carts
• fork lifts
• warehouse carts

Light Electric Vehicle (LEV) options, such as e-scooters and e-bikes, are ideal transportation modes for short trips and small package delivery.  Light Electric Vehicles  such as these are gaining popularity in commercial, retail, and military applications. As such, accidents and injuries related to the use of LEVs are also on the rise.

Our value

We propose that LEVs would benefit greatly from technology that improves the operators situational awareness.  We also propose that a solution can be developed such that the per-unit cost will be appropriate to the (relatively) low cost of the subject vehicle application. The key enabler here is the low speed of the subject vehicles inviting short range (low cost) sensors such a mmWave radar, solid state LiDAR, and Inertial Measurement Units (IMU).. 

Solutions in development

Technology based "situal awareness" for Light Electric Vehicle. The vehicle mounted system consists of sensors, controls, and alerts that provide the operator with extra "eyes on the road".

Solution key features

   1) Sidewalk Detection - Classify riding surface as "sidewalk" or "not sidewalk"

Requirements

The system should determine when the ego vehicle is being