Collision-free socially aware robot navigation

Scope

This research focuses on developing control algorithms for mobile robots to navigate towards a reference target using different on-board sensor measurements, combined through a hybrid dynamical systems framework to ensure stability and robustness of the control algorithms against external perturbations and measurement noises. Additionally, it explores improving robot reliability and efficiency in human-robot interactions, particularly when cooperating with people. One approach considered involves using potential fields with limit cycles and nonlinear opinion dynamics to simulate human non-verbal communication protocols for negotiating space usage.

Expected Outcomes

The expected outcomes of this research include demonstrating the effectiveness of the proposed control strategy in achieving stabilization, even in the presence of significant measurement noise, making it suitable for low-cost sensors. Additionally, the research aims to advance robot navigation in shared spaces by combining reactive behaviors and social rules for distributed robotic systems, while also focusing on controlling robot-human interactions using social opinion dynamics to enhance cooperation in these environments.

Publications and Patents

G. Notomista, G. P. T. Choi, and M. Saveriano, "Reactive Robot Navigation Using Quasi-conformal Mappings and Control Barrier Functions," IEEE Transactions on Control Systems Technology, 2024 (accepted)
R. Ballaben, P. Braun and L. Zaccarian, "Lyapunov-Based Avoidance Controllers With Stabilizing Feedback," in IEEE Control Systems Letters, vol. 8, pp. 862-867, 2024, doi: 10.1109/LCSYS.2024.3404770.
R. Ballaben, A. Astolfi, P. Braun, and L. Zaccarian, "Orchestrating On-Board Sensors For Global Hybrid Robust Stabilization Of Unicycles", accepted for publication in Automatica, 2025.
G. D’Addato, P. Falqueto, L. Palopoli, and D. Fontanelli, "Socially-Aware Opinion-Based Navigation with Oval Limit Cycles," Submitted to 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025.

Personnel

Reference person: Riccardo Ballaben
DII members: Giulia d'Addato (PhD student), Daniele Fontanelli, Luca Zaccarian

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