Planes, trains and automobiles - autonomy for the modern robot

—We are concerned with enabling truly large scale autonomous navigation in typical human environments. To this end we describe the acquisition and modeling of large urban spaces from data that reflects human sensory input. Over 200GB of image and inertial data are captured using head-mounted stereo cameras. This data is processed into a relative map covering 121 km of Southern England. We point out the numerous challenges we encounter, and highlight in particular the problem of undetected ego-motion, which occurs when the robot finds itself on-or-within a moving frame of reference. In contrast to global-frame representations, we find that the continuous relative representation naturally accommodates moving-reference-frames – without having to identify them first, and without inconsistency. Within a moving-reference-frame, and without drift-less global exteroceptive sensing, motion with respect to the global-frame is effectively unobservable. This underlying truth drives us towa...

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Gabe Sibley, Christopher Mei, Ian D. Reid, Paul M. Newman
• Keywords: Continuous Relative Representation, ICRA 2010, Relative Bundle Adjustment, Robotics, Scale Autonomous Navigation