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About

Pilar Bachiller is a robotics researcher whose work spans socially aware robot navigation, cognitive architectures, and human-robot interaction. Her most impactful contribution, a 2024 survey on socially aware robot navigation (80 citations), has become an essential reference for researchers developing robots capable of moving safely and appropriately alongside humans — a challenge central to autonomous vehicles, delivery robots, and assistive systems. Her foundational work on RoboComp (75 citations), a comprehensive tool-based robotics framework, has provided the community with robust infrastructure for building and experimenting with complex robotic systems over more than a decade. Bachiller has consistently pushed the boundaries of robot perception and cognition, contributing graph neural network approaches to model human-aware navigation disruption, distributed working memory architectures for cognitive systems, and visual attention mechanisms that draw on psychological theories of selective processing. Her commitment to education is evident through LearnBlock, a robot-agnostic programming tool designed to bring STEM learning to primary and secondary students worldwide. Across her career, Bachiller has accumulated over 290 citations, reflecting sustained influence across autonomous navigation, perceptual architectures, and the sociotechnical dimensions of human-robot coexistence.