Jonas Ruesch

Papers

Total Citations

146

H-Index

About

Jonas Ruesch is a leading researcher in cognitive robotics, with a primary focus on developing biologically inspired attention systems and spatial models for humanoid robots. His most influential contribution is the multimodal saliency-based bottom-up attention framework for the iCub humanoid robot, which integrates visual and acoustic saliency maps to guide the robot’s eye and neck movements. This work, published in 2008 and cited 133 times, provides a modular, distributed software architecture that fuses sensory inputs, enabling robots to prioritize environmental stimuli in real time—a foundational step toward human-like perception. Ruesch further advanced this line of research by introducing object-level understanding to the iCub’s low-level attention system. In his 2009 work, he defined objects as clusters of SIFT visual features, allowing the robot to store and recognize unknown objects encountered at close range. This spatial model, though less cited, bridges the gap between raw sensory data and meaningful interaction, a critical achievement for social robotics. Ruesch’s work has been instrumental in shaping how humanoid robots perceive and engage with their environment, laying the groundwork for more autonomous, context-aware systems.