Rowcus

What it does

In rowing, athletes have to look back every few strokes, because they are facing backwards. Our device monitors the direction of travel with the help of a sensor and informs the athlete, with an acoustic signal, about obstacles that pose a risk of collision.

Your inspiration

The idea was originally developed by two former ETH students. Their focus was however on the software. They then set us the task of further developing the algorithm and the appropriate product for it. We are both passionate rowers and know the problem well. The rowing market is waiting for such a device.

How it works

A LiDAR sensor (Light Detection and Ranging) is used to detect potential obstacles. This sensor can measure the distance to reflective objects using an infrared laser. Using the laser return times and the speed of light, the distance to the object can be determined to an accuracy of a few centimeters. A LiDAR sensor is suitable for the Rowcus project for several reasons: In comparison to other distance sensors, e.g. ultrasonic sensors, the angular resolution is very high and the range is in the order of 100m. Compared to radar sensors known from nautical applications, LiDAR sensors are small and light enough to be used on a rowing boat. The device can be mounted on the number plate holder and has a 360° LED so that you can row even at dawn. If an obstacle is on a collision course the device will simply inform the athlete by saying "Left" or "Right" over a loudspeaker. He will then know which direction to look and be able to react appropriate to the situation.

Design process

1. Detailed research work: Market, competition, laws, interviews with experts, observations. 2. Combinations of different technologies for the recognition of obstacles and the transmission of information to the athlete. 3. Testing of three solutions on land and water. Evaluate and exclude. The acoustic solution, in which the signal is transmitted directly by the sensor, has clearly prevailed over a haptic or visual solution and has thus been further processed. All functions and their components were defined and a layout of the interior was created. With the help of foam, wood, cardboard and paper, the first form ideas were implemented. It was important to us that the device fits in the environment of rowing, unobtrusive but nevertheless trustworthy. There should be as little additional effort for the athlete as possible. The favorites were sketched in detail and built up in CAD. Various models were printed in 3D to test their effect on the boat. 5. The final shape was digitally constructed, including the inner workings, and optimized for injection molding. These were then 3D printed, reworked and prepared for the final exhibition.

How it is different

Currently there is no product on the market that alerts rowers of obstacles, so that looking back on the boat can be reduced to a minimum and safety is increased. Thanks to our system, athletes are only warned when they need to react so that they can fully focus on the complex movements of rowing. Other solutions such as the head mirror or the camera in combination with the display fog up quickly, dazzle the user and are unusable with low light. Our device can simply be charged with USB and easily used without any previous knowledge, Bluetooth pairing or wiring. Shape and colours harmonize with the unique shape of the boat and the world of rowing.

Future plans

Our goal is to further develop the sensor for production. We have already received a great deal of positive feedback and are convinced that this is a feasible product which could even be installed directly in boats or used for other areas of application in the future. The device could simply be expanded with an acceleration sensor and GPS and thus also be used as a tracker. But to optimize the device for production, to do further tests and to improve the technology as well as the algorithm, we still need financial support. The Dyson Award would be confirmation and help for us and to find potential investors.

Awards

We are nominated for the ZHdK Highlights.