Riccardo Tornese

Innovation Engineering (Italy), Politecnico di Milano

Papers

Total Citations

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About

Riccardo Tornese is a robotics researcher whose work bridges autonomous navigation and machine learning, with a particular focus on maritime and complex robotic systems. His key research areas include obstacle avoidance, simulation environments, and layered learning frameworks for robot control. In his 2022 paper, Tornese developed a ROS-based simulation environment for obstacle avoidance in maritime operations, implementing the Timed Elastic Band (TEB) algorithm to enable safe, real-time path planning for autonomous vessels. This work, which has garnered 4 citations, provides a flexible platform for testing various planning algorithms in challenging maritime settings. Earlier, in his 2009 paper "ESLAS - a robust layered learning framework" (also 4 citations), Tornese tackled the growing complexity of robot programming by proposing a hierarchical approach that separates low-level skill acquisition from high-level strategy selection. This framework simplifies the development of autonomous behaviors in domains where both motor skills and tactical decision-making must be coordinated. Tornese’s contributions are particularly valuable for researchers working on autonomous systems in unstructured environments, offering practical tools and methodologies that reduce programming overhead while improving robustness.