RC Car Racing Challenge

1 Introduction

Time	Team (setting 5min + racing 15min)	Hardware
	ROUND 1
14:00 - 14:20	RONA	rccar 1
14:15 - 14:35	SUPERBOARD	rccar 2
14:30 - 14:50	ROBOLUCK	rccar 1
14:45 - 15:05	KAIROS	rccar 2
15:00 - 15:20	DONGVIGATOR	rccar 1
15:15 - 15:35	TRAECE	rccar 2
	ROUND 2
15:30 - 15:50	RONA	rccar 2
15:45 - 16:05	SUPERBOARD	rccar 1
16:00 - 16:20	ROBOLUCK	rccar 2
16:15 - 16:35	KAIROS	rccar 1
16:30 - 16:50	DONGVIGATOR	rccar 2
16:45 - 17:05	TRAECE	rccar 1
17:10 - 17:20	Score Announcement

	Team Name	Member 1	Member 2	Member 3	Member 4	Member 5
1	TRAECE	Donghwee Son	Gwangjin Kim	Minjun Lee	Chanhyeong Lee
2	KAIROS	Jaesung Kim	Jihoon Han	Mumford Ruby Qian Yue	Tou Sharlene
3	ROBOLUCK	Chanu Hong	Woojun Kang	Ameur Yazid Stephane	Acosta Martinez Maximiliano
4	SUPERBOARD	Hongmo Jung	Younghwan Lee	Hanjun Kim	Euihwan Jeong
5	DONGVIGATOR	Taejung Kim	Jangwon Kim	Taihyoung Rhee	Dongha Hwang
6	RONA	Daeun Lee	Seongje Park	Seongha Kim	Joseph Park	Midem Oh

This contest will show off the autonomous driving with a RC car. Winners will be chosen based on the number of passed waypoints and race completion time in real race tracks.

Date: 2023/12/15 (Friday)
Time: 2:00PM ~
Location: Building 300, room 201(Gym)
More information about previous project leaderboards

1.1 Schedule

2 Goal

The objective of this contest is to encourage entrants to create a robust and fast robot driving policy to control an RC car with LiDAR. Students have to use behavior cloning (GPR) or implement a deep learning algorithm for driving policy. The map of the environment is not given to RC Car, so the RC car needs to estimate its control input using the LiDAR observations. The goal of the contest is to complete race in the fastest time without collision.

3 Details

3.1 Racing Track

3.2 Driving Policy

The driving policy generates an efficient path to race without colliding on track. To generate a proper action that the RC car can follow, dynamics of the RC car (e.g. rotation angle, speed, ...) should be considered while generating actions.