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cs.RO2026

A Formal gatekeeper Framework for Safe Dual Control with Active Exploration

Kaleb Ben Naveed, Devansh R. Agrawal, Dimitra Panagou

Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations, yet ignores uncertainty reduct…

cs.RO2026

Trajectory Planning for Safe Dual Control with Active Exploration

Kaleb Ben Naveed, Manveer Singh, Devansh R. Agrawal +1

Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations, yet ignores uncertainty reduct…

cs.RO2025

Multi-Agent gatekeeper: Safe Flight Planning and Formation Control for Urban Air Mobility

Thomas Marshall Vielmetti, Devansh R Agrawal, Dimitra Panagou

We present Multi-Agent gatekeeper, a framework that provides provable safety guarantees for leader-follower formation control in cluttered 3D environments. Existing methods face a…

cs.RO2025

Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints

Daniel M. Cherenson, Devansh R. Agrawal, Dimitra Panagou

Mission planning can often be formulated as a constrained control problem under multiple path constraints (i.e., safety constraints) and budget constraints (i.e., resource expendit…

cs.RO2025

Adaptive Ergodic Search with Energy-Aware Scheduling for Persistent Multi-Robot Missions

Kaleb Ben Naveed, Devansh R. Agrawal, Rahul Kumar +1

Autonomous robots are increasingly deployed for long-term information-gathering tasks, which pose two key challenges: planning informative trajectories in environments that evolve…

cs.RO2025

Certifiably-Correct Mapping for Safe Navigation Despite Odometry Drift

Devansh R. Agrawal, Taekyung Kim, Rajiv Govindjee +4

Accurate perception, state estimation and mapping are essential for safe robotic navigation as planners and controllers rely on these components for safety-critical decisions. Howe…