Overview

　　In this role, the software engineer 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 experience: embedded software developer, computer engineering, robotics.

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

　　The work will take place on the campus of Lawrence Tech University in Southfield, MI. Specifically, our lab and office are located Here{target="_blank" rel="noopener"}. 

　　The engineer will work with 2-3 other engineers in a team environment.

　　Working hours are flexible.  This is a long-term position.

　　Company

　　GEKOT Robotics 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{target="_blank" rel="noopener"}

　　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 detectionHazard avoidanceLane departure warning/correctionBlind spot detectionThese complex solutions relay on a costly suite of technology which makes them unfeasible for Light Electric Vehicles such as:

　　e-bikeselectric scootersmobility scootersgolf cartsfork liftswarehouse cartsLight 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).

　　Work Activities

　　Identify

　　Learn about concerns with electric scooters: safety and usage rules. Specifically-

　　Accidents/close calls  between scooters and pedestriansAccidents/close calls  between scooters and carsAccidents/close calls  between scooters and other Light Electric VehiclesRules regarding the use of electric scooter on sidewalks and bike lanesReview existing solutions related to these topics

　　Review provided prototypes and previous efforts

　　Design/Create

　　Create an improved design to the solution based on lessons learned from previous efforts.Develop an Alpha (bench) prototype of your solution suitable for lab testing.

　　 Testing

　　Perform extensive testing of your prototype.  Review and refine design.

　　If appropriate, develop a Beta prototype of your solution suitable for "real world" functional testing

　　Create organized and documented embedded software based on provided guidelines