About

I am a Master Student at Delft University of Technology (TU Delft). My research interests are Robotics and Computer Vision. Currently, I am 1st year Master student in Robotics Program.

Interests
  • Computer Vision
  • Robotics
  • Simultaneous Localization and Mapping (SLAM)
  • Autonomous Driving
Education

  • MSc Robotics, 2026 (Expected)

    Delft University of Technology (TU Delft)

  • BEng Mechanical Engineering - Mechatronics, 2024

    Toronto Metropolitan University

Publications

Inverse k-visibility for RSSI-based Indoor Geometric Mapping
IEEE Sensors Journal (Under Review)
Junseo Kim, Matthew Lisondra, Yeganeh Bahoo, Sajad Saeedi
Project Website PDF
M³RS: Multi-agent, Multi-objective, and Multi-mode Routing and Scheduling
IEEE Robotics and Automation Letters (RA-L) (Under Review)
Ishaan Mehta, Junseo Kim, Sharareh Taghipour, Sajad Saeedi
Project Website PDF Simulation Video Hardware Video
Structure from WiFi (SfW): RSSI-based Geometric Mapping of Indoor Environments
The American Control Conference (ACC), 2024
Junseo Kim, Jill Aghyourli Zalat, Yeganeh Bahoo, Sajad Saeedi
Project Website PDF
Visual Inertial Odometry using Focal Plane Binary Features (BIT-VIO)
The International Conference on Robotics and Automation (ICRA), 2024
Matthew Lisondra, Junseo Kim, Riku Murai, Kourosh Zareinia, Sajad Saeedi
Project Website PDF

Projects

Autonomous Truck Navigation With Trailer Integration Via Natural Language Processing
MEC825-Mechanical Design

This project goes through custom 3D CAD modelling, Finite Element Analysis, Sensor Integration, and Natural Language Processing under Robotic Platform.

Project Website Conference Paper Full Final Report
Inliers & Outliers in statistical inference (RANSAC, GNC, ADAPT)
ME8135(State Estimation) - Summer 2023

This project calculates a homography to map points between two images, using algorithms like RANSAC, GNC, and ADAPT to ensure accuracy despite noise and outliers.

PDF Code(RANSAC) Code(GNC) Code(ADAPT)
Estimation Methods with Algorithms for Robotics
ME8135(State Estimation) - Summer 2023

This is the summary of different state estimation methods used in Robotics including Linear Gaussian Estimation, Non-linear Gaussian Estimation, and Outliers.

PDF
Particle Filter (Linear & Non-linear model)
ME8135(State Estimation) - Summer 2023

This project demonstrates the use of a particle filter in both linear and non-linear models. For the linear model, we use a Gaussian distribution as the likelihood function to improve the filter's performance and accuracy.

PDF Code(Linear) Code(Non-Linear) Video(Linear) Video(Non-Linear)
Kalman Filter & Extended Kalman Filter
ME8135(State Estimation) - Summer 2023

This project demonstrates the use of Kalman filter and Extended kalman filter with simulations.

PDF Code(KF) Code(EKF_Linear) Code(EKF_Non-Linear) Video(KF) Video(EKF_Linear) Video(EKF_Non-Linear)
YOLO V8 with Intel Realsense D435i Camera
Autonomous Vehicles Laboratory

This project uses YOLO V8 algorithms measures the depth of the objects based on the segmentation points without using boundary box.

Code(Segmentation) Code(Boundary Box)
Monte Carlo Simulation & Probability Density Function (PDF)
ME8135(State Estimation) - Summer 2023

This project uses Montel Carlo simulation to plot the uncertainty ellipses for different random variables.

PDF Code(Monte Carlo) Code(PDF)

Contact