Range Constraint

Range constraint, in various scientific contexts, refers to limitations imposed on the operational scope or output of a system or model. Current research focuses on incorporating these constraints into diverse applications, including multi-robot task allocation (using auction-based algorithms and efficient path planners), machine learning model safety (through anomaly detection and operational range bounding), and image processing (via Fourier-based methods and loss functions that incorporate spatial and frequency constraints). Addressing range constraints is crucial for improving the reliability, efficiency, and generalizability of models across different domains, with significant implications for robotics, machine learning, and computer vision.