cs.ROSep 19, 2026

Density-Driven Area Coverage for Nonholonomic Multi-Robot Systems with Safety Guarantee

Authors: Julian Martinez, Kooktae Lee

Organizations: Department of Mechanical and Aerospace Engineering, Texas Tech University, Lubbock, TX 79409, USA

Abstract

Density-Driven Optimal Control (D2OC) provides a principled approach to distributing multi-robot teams over non-uniform spatial distributions. Applying D2OC to nonholonomic robots, however, creates a gap between safety constraints imposed on a reference motion and the physical inputs that determine the actual robot motion. We address this issue by enforcing the safety constraint directly on the robot's physical inputs while preserving the density-driven coverage objective. The proposed framework combines D2OC with a control barrier function safety filter through a feedback-linearizing look-ahead point, allowing safety and actuator limits to be considered together during control. We further derive a safety margin that accounts for the look-ahead geometry, robot footprint, and motion during each control interval. Simulation results show that the proposed method maintains the required physical separation while achieving coverage performance comparable to a conventional reference-tracking approach, which can satisfy safety on the reference motion yet violate the corresponding physical clearance. Experiments on multiple nonholonomic robots in the Robotarium further demonstrate safe execution while driving the robots toward the desired spatial distribution. These results show that enforcing safety directly on the physical inputs can eliminate the mismatch between safety certification and physical robot motion in density-driven multi-robot coverage.

Figures & tables

Explore similar work

CardsList
  1. Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

    Oct 3, 2026Julian Martinez, Kooktae LeeMulti-Agent ControlOptimal Control

  2. Safe and Energy-Aware Multi-Robot Density Control via PDE-Constrained Optimization for Long-Duration Autonomy

    Apr 16, 2026Longchen Niu, Andrew Nasif, Gennaro NotomistaRobotic ControlMulti-Robot Systems

  3. Density-Driven Optimal Control: Convergence Guarantees for Stochastic LTI Multi-Agent Systems

    Apr 9, 2026Kooktae LeeMulti-Agent ControlStochastic Optimal Control