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About

Bram Bolder is a robotics researcher whose work centers on humanoid robot cognition, autonomous learning, multimodal perception, and dexterous manipulation. His most influential contributions emerge from the development of the Autonomous Learning and Interacting System (ALIS), an evolving platform implemented on Honda's ASIMO robot that enables machines to learn and interact with their environment in open-ended, human-inspired ways. Through successive ALIS iterations, Bolder advanced systems capable of integrating visual and auditory signals, self-collision-free motion control, and infant-inspired audio-visual association learning — without requiring intrusive hardware like headsets. His 2007 work on visually guided whole-body interaction (30 citations) established a foundational framework linking stabilized visual "proto-objects" to fluid, reactive robot motion. Complementary research on fast planar surface detection (21 citations) addressed the practical demands of robots navigating human-made environments. Later work on in-hand dexterous manipulation introduced feedback-based and finite-state-machine strategies for handling objects with unknown physical properties. Collectively spanning developmental robotics, cognitive systems, and real-world manipulation, Bolder's research reflects a sustained commitment to building robots that learn, perceive, and act with increasing autonomy and adaptability.