Receive KAIST news by email!
Type your e-mail address here.
by recently order
by view order
Team KAIST to Race at CES 2022 Autonomous Challenge
Five top university autonomous racing teams will compete in a head-to-head passing competition in Las Vegas A self-driving racing team from the KAIST Unmanned System Research Group (USRG) advised by Professor Hyunchul Shim will compete at the Autonomous Challenge at the Consumer Electronic Show (CES) on January 7, 2022. The head-to-head, high speed autonomous racecar passing competition at the Las Vegas Motor Speedway will feature the finalists and semifinalists from the Indy Autonomous Challenge in October of this year. Team KAIST qualified as a semifinalist at the Indy Autonomous Challenge and will join four other university teams including the winner of the competition, Technische Universität München. Team KAIST’s AV-21 vehicle is capable of driving on its own at more than 200km/h will be expected to show a speed of more than 300 km/h at the race.The participating teams are:1. KAIST2. EuroRacing : University of Modena and Reggio Emilia (Italy), University of Pisa (Italy), ETH Zürich (Switzerland), Polish Academy of Sciences (Poland) 3. MIT-PITT-RW, Massachusetts Institute of Technology, University of Pittsburgh, Rochester Institute of Technology, University of Waterloo (Canada)4.PoliMOVE – Politecnico di Milano (Italy), University of Alabama 5.TUM Autonomous Motorsport – Technische Universität München (Germany) Professor Shim’s team is dedicated to the development and validation of cutting edge technologies for highly autonomous vehicles. In recognition of his pioneering research in unmanned system technologies, Professor Shim was honored with the Grand Prize of the Minister of Science and ICT on December 9. “We began autonomous vehicle research in 2009 when we signed up for Hyundai Motor Company’s Autonomous Driving Challenge. For this, we developed a complete set of in-house technologies such as low-level vehicle control, perception, localization, and decision making.” In 2019, the team came in third place in the Challenge and they finally won this year. For years, his team has participated in many unmanned systems challenges at home and abroad, gaining recognition around the world. The team won the inaugural 2016 IROS autonomous drone racing and placed second in the 2018 IROS Autonomous Drone Racing Competition. They also competed in 2017 MBZIRC, ranking fourth in Missions 2 and 3, and fifth in the Grand Challenge. Most recently, the team won the first round of Lockheed Martin’s Alpha Pilot AI Drone Innovation Challenge. The team is now participating in the DARPA Subterranean Challenge as a member of Team CoSTAR with NASA JPL, MIT, and Caltech. “We have accumulated plenty of first-hand experience developing autonomous vehicles with the support of domestic companies such as Hyundai Motor Company, Samsung, LG, and NAVER. In 2017, the autonomous vehicle platform “EureCar” that we developed in-house was authorized by the Korean government to lawfully conduct autonomous driving experiment on public roads,” said Professor Shim. The team has developed various key technologies and algorithms related to unmanned systems that can be categorized into three major components: perception, planning, and control. Considering the characteristics of the algorithms that make up each module, their technology operates using a distributed computing system. Since 2015, the team has been actively using deep learning algorithms in the form of perception subsystems. Contextual information extracted from multi-modal sensory data gathered via cameras, lidar, radar, GPS, IMU, etc. is forwarded to the planning subsystem. The planning module is responsible for the decision making and planning required for autonomous driving such as lane change determination and trajectory planning, emergency stops, and velocity command generation. The results from the planner are fed into the controller to follow the planned high-level command. The team has also developed and verified the possibility of an end-to-end deep learning based autonomous driving approach that replaces a complex system with one single AI network.
KI-Robotics Wins the 2021 Hyundai Motor Autonomous Driving Challenge
Professor Hyunchul Shim’s autonomous driving team topped the challenge KI-Robotics, a KAIST autonomous driving research team led by Professor Hyunchul Shim from the School of Electric Engineering won the 2021 Hyundai Motor Autonomous Driving Challenge held in Seoul on November 29. The KI-Robotics team received 100 million won in prize money and a field trip to the US. Out of total 23 teams, the six teams competed in the finals by simultaneously driving through a 4km section within the test operation region, where other traffic was constrained. The challenge included avoiding and overtaking vehicles, crossing intersections, and keeping to traffic laws including traffic lights, lanes, speed limit, and school zones. The contestants were ranked by their order of course completion, but points were deducted every time they violated a traffic rule. A driver and an invigilator rode in each car in case of an emergency, and the race was broadcasted live on a large screen on stage and via YouTube. In the first round, KI-Robotics came in first with a score of 11 minutes and 27 seconds after a tight race with Incheon University. Although the team’s result in the second round exceeded 16 minutes due to traffic conditions like traffic lights, the 11 minutes and 27 seconds ultimately ranked first out of the six universities. It is worth noting that KI-Robotics focused on its vehicle’s perception and judgement rather than speed when building its algorithm. Out of the six universities that made it to the final round, KI-Robotics was the only team that excluded GPS from the vehicle to minimize its risk. The team considered the fact that GPS signals are not accurate in urban settings, meaning location errors can cause problems while driving. As an alternative, the team added three radar sensors and cameras in the front and the back of the vehicle. They also used the urban-specific SLAM technology they developed to construct a precise map and were more successful in location determination. As opposed to other teams that focused on speed, the KAIST team also developed overtaking route construction technology, taking into consideration the locations of surrounding cars, which gave them an advantage in responding to obstacles while keeping to real urban traffic rules. Through this, the KAIST team could score highest in rounds one and two combined. Professor Shim said, “I am very glad that the autonomous driving technology our research team has been developing over the last ten years has borne fruit. I would like to thank the leader, Daegyu Lee, and all the students that participated in the development, as they did more than their best under difficult conditions.” Dae-Gyu Lee, the leader of KI-Robotics and a Ph.D. candidate in the School of Electrical Engineering, explained, “Since we came in fourth in the preliminary round, we were further behind than we expected. But we were able to overtake the cars ahead of us and shorten our record.”
마지막 페이지 1
KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Copyright(C) 2020, Korea Advanced Institute of Science and Technology,
All Rights Reserved.