Main interests: Visual Navigation and Calibration. Navigation of wheeled, legged or humanoid robots requires keeping some sort of continuous self-calibration based on proprioceptive data combined with vision or inertial sensors. Most approaches rely on exteroception for unknown or dynamic environments or on full environment reconstruction (e.g. SLAM), at the cost of prohibitive computational resources. Instead, we will explore the use of customized vision sensors, topological, appearance-based representations and attention mechanisms to develop efficient navigation systems, with a parsimonious use of hardware and computational resources. We will further develop the use and design of novel, non-conventional cameras, combining different reflective surfaces with lenses, space-variant imaging, different sensitivity spectra, depth sensing, aggregation of multiple cameras, and active light projection.