SICK Inc., is excited to announce a challenge for universities across the nation to support innovation and student achievement in automation and technology. Twenty teams will be selected to participate in the challenge and the chosen teams will be supplied with a SICK 270° lidar (TiM) and accessories. The teams will be challenged to solve a problem, create a solution and bring a new application that utilizes the SICK scanner in any industry.
TiM$10K challenge registration is closed for the 2020-2021 school year.
About the TiM
From advanced manufacturing to automated vehicles and self-driving cars, engineers are using lidar to change the world as we know it. One of the fastest-growing markets for lidar, however, is in primary, secondary, and end-of-line packaging. As the usability of lidar has increased while the price has decreased, lidar is becoming ever more instrumental in ensuring the quality and efficiency of packaging processes at the world’s biggest companies.
The 3 winning teams will win a cash award of
2020 TiM$10K Challenge Winners
First Place:Worcester Polytechnic Institute
Team 1 from Worcester Polytechnic Institute, created an innovative product called the ROADGNAR. The ROADGNAR detects, analyzes, and measures potholes, cracks, and other things that cause roadways to be in poor condition. With this data, local governments can better prioritize what roads need to be repaired first based on the condition.
Second Place: University of Illinois at Urbana-Champaign
The second place team, University of Illinois at Urbana-Champaign, developed the L-PUPP, a device intended to detect when a theft is occurring at a construction site. The L-PUPP, or LiDAR Portable Ultimate Protection Product, can be installed all around a construction site to detect any unauthorized breaches onto the site.
Third Place: Rochester Institute of Technology
The third place team from Rochester Institute of Technology created a solution that uses a 2D LiDAR sensor and a camera to extend single beam LiDAR to full resolution. With this solution, companies using automated mobile robots can use a less cost prohibitive solution that also provides a comparatively higher resolution at a much faster rate, with the ability to determine per-pixel depth.