Curriculum Vitae
General Information
| Full Name | Justin M. Kottinger | 
| Date of Birth | 23rd October 1997 | 
| Languages | English | 
Education
-  2024Ph.D in RoboticsUniversity of Colorado Boulder, CO- Department of Robotics
 
-  2024M.S in Aerospace EngineeringUniversity of Colorado Boulder, CO- Concentration in Autonomous Systems / Robotics
 
-  2019B.A in PhysicsWhittier College, Whittier, CA- Minor in Mathematics
- Member of Sigma Pi Sigma and Pi Mu Epsilon
 
Skills
-  Programming Languages- C++
- Python
- MATLAB
- Julia
 
-  Modeling and Simulation- ROS / ROS 2
- Gazebo
- Simulink
 
-  Operating Systems- Mac OS
- Linux
- Windows
 
-  Workflow- Git
- GitHub
- Bitbucket
- Jira
 
Relevant Coursework
-  Core Courses- Linear Control Theory
- Mathematical Statistics
- Statistical Estimation
- Decision Making Under Uncertainty
- Spacecraft Attitude, Dynamics, and Control
 
-  Research Specific Courses- Algorithmic Motion Planning
- Statistical Learning
- Verifcation and Synthesis of Stochastic Systems
- Coordination and Control of Multi-Agent Systems
- Hybrid Control Systems
 
Experience
-  2023-presentRobotic Navigation Software Engineer Graduate InternTrimble Corporation, Westminster, Colorado, USA- Conceptualized and developed a containerized physics-based simulator using Docker, ROS2, and Gazebo to test GNC service product.
- Implemented motion planning algorithms for line acquisition of autonomous agricultural vehicles.
- Enabled autonomous line acquisition in reverse and validated on-vehicle.
 
-  2022-2023Fault Identification of Autonomous Systems via Bayesian InferenceUniversity of Colorado Boulder, Colorado, USA- Utilized Bayesian hypothesis testing to accurately identify faults and unknown anomalies within autonomous robots.
- Implemented statistical estimation algorithms such as Kalman Filter, Extended Kalman Filter, and Unscented Kalman Filter in C++.
- Conceptualized and implemented moving time-windows and fault-partitioning to improve the baseline approach by 20%.
- Delivered a final product that identified faults and unknown anomalies with over 95% success.
 
-  2021-2022Autonomous Systems Software Engineer Graduate InternThe Aerospace Corporation, El Segundo, California, USA- Assisted in design, control, and system identification of an omni-directional octocopter.
- Implemented advanced algorithms and data structures to create novel flight software in Python and C++.
- Validated custom flight modules inside simulation using ROS and Gazebo, and tested them onboard the vehicle.
- Assisted in the development of a Risk-Aware framework for Uber ATG's self-driving vehicle stack.
- Formulated probabilistic dynamics propagation and intent models for self-driving vehicle and pedestrian models.
- Implemented probabilistic models in Python and C++ using Bayesian derived statistics.
 
Presentations
-  2022- Conflict‐based Search for Multi‐Robot Motion Planning with Kinodynamic Constraints
- International Conference On Intelligent Robots and Systems (IROS)
 
-  2022- Explainable Multi-Robot Motion Planning
- Robotics Summer Seminar
 
-  2022- Conflict‐Based Search for Explainable Multi‐Agent Path Finding
- International Conference on Automated Planning and Scheduling (ICAPS)
 
-  2021- MAPS‐X -- Explainable Multi‐Robot Motion Planning via Segmentation
- International Conference on Robotics and Automation (ICRA)
 
Achievements
-  2021- Recipient, Graduate Assistantships for Areas of National Need (GAANN) Fellowship
 
-  2019- Recipient, Undergraduate Award for Outstanding Academic Performance in the Major
- Recipient, Magna Cum Laude Honors
 
-  2018- 2nd Place, Research Presentation Competition at NSF funded REU
- Captain, Whittier College NCAA Baseball Team
 
Open Source Projects
-  2023-nowMulti-Robot OMPL- An extended version of the reverered Open Motion Planning Library (OMPL) designed for decoupled multi-robot motion planning.
 
-  2022-nowKinodynamic Conflict-Based Search (K-CBS)- A scalable and generalizable decoupled multi-robot motion planning algorithm that provides completeness guarantees.