Welcome to the website of the Mobility Systems and Control (MSC) Lab in Chung-Ang University. The research in our lab focuses on the sensing, estimation and control algorithms with applications to intelligent mobility systems. Sensing, estimation, and control are important research areas that will play a critical role in bringing intelligent robots and transportation systems into the real world. My long-term research goals are to develop sensors, estimation algorithms and controllers that provide practical solutions for mobile robot navigation, robot/vehicle pose estimation and autonomy and safety enhancement in intelligent mobility systems.

모빌리티 시스템 및 제어 연구실은 센싱, 추정 그리고 제어 이론 연구를 진행하고 있으며, 지능형 모빌리티 시스템 관련 응용 분야를 연구하고 있습니다.

A novel navigation system using driving state classification algorithm for semi-autonomous tractors

Deep Reinforcement Learning-Based Active Sensing on a Bicycle for Vehicle Tracking

Interacting Multiple-Model Method for Fault Detection and Short Resistance Estimation in Parallel Connected Lithium-ion Batteries

Adaptive Kalman Filter-Based Fusion of Multiple Low-Cost IMUs for Mobile Robot Navigation

Clustering and Investigation of Human Driving Behavior Using Autoencoder and Risk Assessment

Health Monitoring of In-Cylinder Sensors and Fuel Injectors Using an External Accelerometer

A smart e-scooter with embedded estimation of rear vehicle trajectories for rider protection

Comprehensive analysis of an air-conditioning system based on radiative cooling for building energy savings

LMI-Based Neural Observer for State and Nonlinear Function Estimation

MCHeart: Multi-Channel-Based Heart Signal Processing Scheme for Heart Noise Detection Using Deep Learning

Accelerometer-Based Robust Estimation of In-Cylinder Pressure for Cycle-to-Cycle Combustion Control

Simultaneous State Estimation and Tire Model Learning for Autonomous Vehicle Applications

Simultaneous Cyber-Attack Detection and Radar Sensor Health Monitoring in Connected ACC Vehicles

A Smart Bicycle That Protects Itself: Active sensing and estimation for car-bicycle collision prevention

Low-Density Lidar Based Estimation System for Bicycle Protection

Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring

On the Need for Switched-Gain Observers for Non-Monotonic Nonlinear Systems

Active Sensing on a Bicycle for Simultaneous Search and Tracking of Multiple Rear Vehicles

Tracking of Vehicle Motion on Highways and Urban Roads Using a Nonlinear Observer

Rear Vehicle Tracking on a Bicycle Using Active Sensor Orientation Control

Design and Control Method for a High-Mobility In-Pipe Robot with Flexible Links

Rear Vehicle Tracking on a Smart E-Scooter

Vehicle Motion Estimation Using A Switched Gain Nonlinear Observer

Resilient Control Under Cyber-Attacks in Connected ACC Vehicles

Nonlinear Observer for Vehicle Motion Tracking

H∞ Observer for Descriptor Nonlinear Systems with Nonlinear Output Equations

Two-Dimensional Active Sensing System for Bicyclist-Motorist Crash Prediction

Active Sensing on a Bicycle for Accurate Tracking of Rear Vehicle Maneuvers

A Novel Collision Avoidance System for Bicycles

Development of high mobility in-pipe inspection robot

Instantaneous kinematic analysis for a crawler type in-pipe robot

Method For Estimating Vehicle Condition, Device For Performing Same, and Recording Medium (차량 상태 추정 방법, 이를 수행하는 장치 및 기록 매체)

Compression Ignition Engine Control

Collision Detection

In-Pipe Inspection Robot

In Pipe Driving Robot (관 내 이동용 로봇)

IMU/GPS 통합 항법 시스템을 위한 최적화 기반 추정 방법 비교 연구

차량 추적을 위한 강화학습 기반 도로변 센서 시스템

자율주행 농기계를 위한 LSTM기반의 주행 상태 분류 알고리즘

컴퓨터 비전 기술과 2D 라이다 융합을 통한 장애물 감지 및 위치 추정

End-to-End 학습 기반의 장애물 회피 주행 연구

2D 라이다와 단안 카메라를 이용한 차량 추적 시뮬레이션 환경구현

농기계 자율주행을 위한 ROS 기반의 항법시스템 구현 및 실험

Mobility Systems and Control Lab (MSC Lab)

교수님 소개

전웅선

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

A novel navigation system using driving state classification algorithm for semi-autonomous tractors

Deep Reinforcement Learning-Based Active Sensing on a Bicycle for Vehicle Tracking

Interacting Multiple-Model Method for Fault Detection and Short Resistance Estimation in Parallel Connected Lithium-ion Batteries

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

전웅선

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

A novel navigation system using driving state classification algorithm for semi-autonomous tractors

Deep Reinforcement Learning-Based Active Sensing on a Bicycle for Vehicle Tracking

Interacting Multiple-Model Method for Fault Detection and Short Resistance Estimation in Parallel Connected Lithium-ion Batteries

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집