State Estimation Intern (Summer)

REGENT•North Kingstown, RI

About The Position

REGENT’s perception team is exploring how multiple Seagliders can share sensor information to build a more complete understanding of their surroundings. The intern will investigate existing multi-agent information-fusion approaches, then design or adapt an algorithm suited to REGENT’s platform and demonstrate its performance using simulations and, where available, real data. This is greenfield work with a defined deliverable, a named mentor, and weekly check-ins. Simulation work will reflect real platform and sensor characteristics, and the intern will present findings to the perception team at the end of the term.

Requirements

A solid foundation in probability theory, statistics, and linear algebra.
Familiarity with state-estimation concepts, such as the Kalman filter, through coursework or project experience.
Comfort using Python or MATLAB to build simulations and analyze results.
Strong analytical thinking and the ability to communicate technical conclusions clearly.
Self-motivation, curiosity, and readiness to learn quickly on a new project.
Ability to collaborate and communicate effectively with engineers, stakeholders, and cross-functional teams.
Adaptability in a fast-paced, changing startup environment.

Responsibilities

Research existing approaches to multi-agent and distributed information fusion.
Propose or adapt an algorithm for combining sensor data from multiple Seagliders into a shared environmental picture.
Build simulation environments in Python or MATLAB that reflect real platform and sensor characteristics.
Test and validate the algorithm in simulation and, where available, against real data; refine the approach based on results.
Work with a dedicated mentor through weekly check-ins.
Communicate technical findings clearly so others on the team can understand and build on them.
Present the algorithm and results to the perception team at the end of the term.