For the third year, SICK invited students from universities around the country to participate in the TiM$10K Challenge. The challenge started in 2018 to support innovation and student achievement in automation and technology.
Teams were supplied with a 270° SICK LiDAR sensor (TiM) and accessories and challenged to solve a problem, create a solution, or bring a new application to any industry that utilizes the SICK LiDAR.
The winners of the TiM$10K Challenge are:
· 1st Place: Texas A&M University (TAMU) Team 2 – AutoTool (automated, robotic tool carrier for the construction industry)
· 2nd Place: Texas A&M University (TAMU) Team 3 – Farm Field Scanning (drone for surveying farmland)
· 3rd Place: University of Wisconsin – Madison (UW Madison) & Worcester Polytechnic Institute (WPI) –LiDAR LiDAR Tunnel Inspection Automation System (LTIAS)
· Honorable Mention: University of Alabama – The MiniMap (3D scanning tool)
“When I think back to where this all started, it was an idea spurred from a problem in the construction industry. The support that the SICK team provided us was incredible, beyond just the amazing technology, but also being there for us when we needed help,” said Mason Kleinecke, a mechanical engineering student at TAMU and a member of the winning team of TiM$10K Challenge. “One example was when we decided to add tool tracking to our device. The SICK team offered an RFID sensor, in addition to the TiM LiDAR they had already provided, and that was amazing. SICK was incredibly helpful, and it’s been a key part of the success of this project.”
The first-place team, Team 2 from TAMU, created a solution for a common problem in the construction industry. Tool inaccessibility and misplacement accounts for 18% of a construction worker’s workday, resulting in wasted time traveling between tool storage and work areas or tools be lost or left behind. The AutoTool provides workers an automated robotic tool carrier to carry tools, automatically follow a worker, and keep an inventory of tools.
The second-place team, Team 3 from TAMU, focused on providing support for large acreage industrial farms with crop growth modeling and tracking. The TYTO Farm Survey System uses SICK LiDAR on a drone to survey acres of farmland and monitor the growth of crops.
The third-place team from UW – Madison, and WPI, invented a LiDAR-based tunnel inspection automation system. With this tool, the inspection of the functionality and safety of tunnels and pipelines can be more easily monitored with less dependence on human labor in hazardous environments.
Finally, the team from UA received an honorable mention for their innovative product that aims to decrease the cost of precise 3D scanning by utilizing a novel application of 2D LiDAR technology.
“LiDAR is somewhat of a special technology, and these projects help bring it to the masses,” said SICK, Inc. CEO Tony Peet. “All of our participants this year have strong business cases to bring innovative ideas to the market.”
Each team was asked to submit a video and paper for judging upon completion of the project. A panel of judges decided the winning submissions based on creativity and innovation, ability to solve a customer problem, commercial potential to productize and market the application, entrepreneurship of the team, and reporting.
The three winning teams win a cash award of $10K for first place, $5K for second place, and $3K for third place. In addition to bragging rights and the cash prize, the first place team, along with the advising professor, will go on an all-expense paid trip to Germany to visit the SICK headquarters and manufacturing facility.
LiDAR Sensor Technology
The LiDAR sensor (TiM) provided to teams utilizes a rotating pulsed laser to calculate distances to its surroundings based on the time-of-flight principle. The rotating laser effectively forms a circle around the TiM, inside which users can create individual fields to monitor for the presence or absence of an object. The reliability of the sensor is improved by SICK’s patented High-Definition Distance Measurement (HDDM) technology, which samples each measurement several times and averages the results.
As the TiM$10K teams ably proved, monitoring the individual fields for objects can be a great way to solve applications that other sensing technologies cannot. This makes the TiM invaluable in a variety of industrial applications, as well as building automation, stationary, and mobile applications. In addition, the integrated Ethernet interface allows for remote monitoring, measurement, and navigation which presented a ton of creative possibilities for the TiM$10K teams.