Robust Trajectory Generation and Control for Quadrotor Motion Planning with Field-of-View Control Barrier Certification

2025-02-03

AI Summary

To address communication outages and perceptual uncertainty in multi-UAV cooperative navigation, this paper proposes a communication-free, real-time distributed motion planning and control framework. The method integrates robust continuous-time trajectory generation with controller synthesis, rigorously certified via Control Barrier Functions (CBFs). It introduces an MPC-CBF discrete optimization architecture incorporating a linear surrogate model of high-order CBF constraints to ensure computational efficiency and real-time execution. Additionally, visual field constraints are encoded as CBFs to guarantee persistent inter-vehicle visibility, thereby enhancing distributed localization robustness. Simulation results demonstrate successful coordination among ten UAVs; hardware experiments validate deployment on two custom-built quadrotors—maintaining stable visual contact even during transient tracking loss. The approach significantly improves system safety and reliability under communication-limited and perception-uncertain conditions.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Intelligent Robots: Motion and Path Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Many approaches to multi-robot coordination are susceptible to failure due to communication loss and uncertainty in estimation. We present a real-time communication-free distributed algorithm for navigating robots to their desired goals certified by control barrier functions, that model and control the onboard sensing behavior to keep neighbors in the limited field of view for position estimation. The approach is robust to temporary tracking loss and directly synthesizes control in real time to stabilize visual contact through control Lyapunov-barrier functions. The main contributions of this paper are a continuous-time robust trajectory generation and control method certified by control barrier functions for distributed multi-robot systems and a discrete optimization procedure, namely, MPC-CBF, to approximate the certified controller. In addition, we propose a linear surrogate of high-order control barrier function constraints and use sequential quadratic programming to solve MPC-CBF efficiently. We demonstrate results in simulation with 10 robots and physical experiments with 2 custom-built UAVs. To the best of our knowledge, this work is the first of its kind to generate a robust continuous-time trajectory and controller concurrently, certified by control barrier functions utilizing piecewise splines.

Problem

• Multi-robot Control
• Vision-based Navigation
• Path Safety Verification

Innovation

• Multi-robot System
• Signal-free Navigation
• Sight-based Control Method