CA0280: Internship - Autonomous Patrolling with Mobile Robot Teams
About The Position
MERL is seeking a highly motivated graduate student to develop closed-loop planning methods for mobile robot teams in autonomous patrolling and persistent monitoring applications, subject to constraints (e.g., battery recharging and localization of unknown, dynamic targets). The intern will collaborate closely with MERL researchers to develop these methods by leveraging approaches for constrained trajectory optimization and multi-agent control. The internship is expected to produce results suitable for top-tier publications. The internship will start in Spring or Summer 2026 and last 3-6 months, depending on scope and progress. Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, or other evidence of proficiency.
Requirements
- Current enrollment in a PhD program in ME/EE/CS/AE, or related programs, with a focus on robotics and/or control systems and published 1-2 high quality conference/journal papers.
- Experience in some of: trajectory optimization algorithms, control design with logical specifications, multi-agent control, and receding-horizon control.
- Strong programming skills in Python and/or C/C++.
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
