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Elia Trevisan

7 accepted papers

2025

Active Disturbance Rejection Control for Trajectory Tracking of a Seagoing USV: Design, Simulation, and Field Experiments

IROS 2025

Unmanned Surface Vessels (USVs) face significant control challenges due to uncertain environmental disturbances like waves and currents. This paper proposes a trajectory tracking controller based on Active Disturbance Rejection Control (ADRC) implemented on the DUS V2500. A custom simulation incorpo

Cited by 1SourceScholar
2025

Dynamic Risk-Aware MPPI for Mobile Robots in Crowds via Efficient Monte Carlo Approximations

IROS 2025

Deploying mobile robots safely among humans requires the motion planner to account for the uncertainty in the other agents’ predicted trajectories. This remains challenging in traditional approaches, especially with arbitrarily shaped predictions and real-time constraints. To address these challenge

Cited by 6SourceScholar
2025

Sampling-Based Model Predictive Control Leveraging Parallelizable Physics Simulations

RA-L 2025

We present a sampling-based model predictive control method that uses a generic physics simulator as the dynamical model. In particular, we propose a Model Predictive Path Integral controller (MPPI) that employs the GPU-parallelizable IsaacGym simulator to compute the forward dynamics of the robot a

Cited by 15SourcecodeScholar
2024

Biased-MPPI: Informing Sampling-Based Model Predictive Control by Fusing Ancillary Controllers

RA-L 2024

Motion planning for autonomous robots in dynamic environments poses numerous challenges due to uncertainties in the robot's dynamics and interaction with other agents. Sampling-based MPC approaches, such as Model Predictive Path Integral (MPPI) control, have shown promise in addressing these complex

Cited by 42SourceScholar
2024

Multi-Modal MPPI and Active Inference for Reactive Task and Motion Planning

RA-L 2024

Task and Motion Planning (TAMP) has made strides in complex manipulation tasks, yet the execution robustness of the planned solutions remains overlooked. In this work, we propose a method for reactive TAMP to cope with runtime uncertainties and disturbances. We combine an Active Inference planner (A

Cited by 20SourceScholar
2023

Multi-Agent Path Integral Control for Interaction-Aware Motion Planning in Urban Canals

ICRA 2023poster

Autonomous vehicles that operate in urban environments shall comply with existing rules and reason about the interactions with other decision-making agents. In this paper, we introduce a decentralized and communication-free interaction-aware motion planner and apply it to Autonomous Surface Vessels…

Cited by 18SourcecodeScholar
2022

Regulations Aware Motion Planning for Autonomous Surface Vessels in Urban Canals

ICRA 2022poster

In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs) that accounts for dynamic and static obstacles. Ou…

Cited by 11SourceScholar