Abstract :
Mobile robots pose a unique set of challenges to artificial intelligence researchers. Such challenges include issues of autonomy, uncertainty (both sensing and control), and reliability, which are all constrained by the discipline that the real world imposes. Planning, sensing, and acting must occur in concert and in context. That is, information processing must satisfy not only the constraints of logical correctness but also some assortment of crosscutting, physical constraints. Particularly interesting among these robots are humanoids, which assume an anthropomorphic (humanlike) form. A growing number of roboticists believe that the human form provides an excellent platform on which to enable interactive, real-world machine learning. As we review successes and failures in the field, we provide a contextual backdrop for understanding where humanoid research began, the dilemmas with which it currently struggles, and where it might take us in the future. We also discuss how these technological developments have and will continue to affect the ways in which we understand ourselves.
