pipeline for mobile depth that supports a wide array of mobile phones, and uses only the existing monocular color sensor. Through several technical contributions, we provide the ability to compute low latency dense depth maps using only a single CPU core of a wide range of (medium-high) mobile phones. We demonstrate the capabilities of our approach on high-level AR applications including real-time navigation and shopping.
This paper presents a vision of humanoid robots as human's key partners in future space exploration, in particular for construction, maintenance/repair and operation of lunar/planetary habitats, bases and settlements. It integrates this vision with the recent plans for human and robotic exploration, aligning a set of milestones for operational capability of humanoids with the schedule and phases of Human space flight system development program for the next decades. These milestones relate to a set of incremental challenges, for the solving of which new humanoid technologies are needed. A system of systems integrative approach that would lead to readiness of cooperating humanoid crews is sketched. Robot fostering, training/education techniques, and improved cognitive/sensory/motor development techniques are considered essential elements for achieving intelligent humanoids. A pilot project in this direction is outlined.
A low-cost vehicle test-bed system was developed to iteratively test, refine and demonstrate navigation algorithms before attempting to transfer the algorithms to more advanced rover prototypes. The platform used here was a modified radio controlled (RC) car. A microcontroller board and onboard laptop computer allow for either autonomous or remote operation via a computer workstation. The sensors onboard the vehicle represent the types currently used on NASA-JPL rover prototypes. For dead-reckoning navigation, optical wheel encoders, a single axis gyroscope, and 2-axis accelerometer were used. An ultrasound ranger is available to calculate distance as a substitute for the stereo vision systems presently used on rovers. The prototype also carries a small laptop computer with a USB camera and wireless transmitter to send real time video to an off-board computer. A real-time user interface was implemented that combines an automatic image feature selector, tracking parameter controls, streaming video viewer, and user generated or autonomous driving commands. Using the test-bed, real-time landmark tracking was demonstrated by autonomously driving the vehicle through the JPL Mars yard. The algorithms tracked rocks as waypoints. This generated coordinates calculating relative motion and visually servoing to science targets. A limitation for the current system is serial computing-each additional landmark is tracked in order-but since each landmark is tracked independently, if transferred to appropriate parallel hardware, adding targets would not significantly diminish system speed.
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