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We present an illumination-robust visual localization algorithm for Astrobee, a free-flying robot designed to autonomously navigate on the International Space Station (ISS). Astrobee localizes with a monocular camera and a pre-built sparse map composed of natural visual features. Astrobee must perform tasks not only during the day, but also at night when the ISS lights are dimmed. However, the localization...
We present the localization approach for Astrobee, a new free-flying robot designed to navigate autonomously on the International Space Station (ISS). Astrobee will accommodate a variety of payloads and enable guest scientists to run experiments in zero-g, as well as assist astronauts and ground controllers. Astrobee will replace the SPHERES robots which currently operate on the ISS, whose use of...
Recently, ridesharing mobile applications, which dynamically match passengers to drivers, have begun to gain popularity. These services have the potential to fill empty seats in cars, reduce emissions and enable more efficient transportation. Ridesharing services become even more practical as robotic cars become available to do all the driving. In this work, we propose rideshare services which transfer...
We have deployed a fleet of robots that pickup and deliver items requested by users in an office building. Users specify time windows in which the items should be picked up and delivered, and send in requests online. Our goal is to form a schedule which picks up and delivers the items as quickly as possible at the lowest cost. We introduce an auction-based scheduling algorithm which plans to transfer...
In 2009, the Lunar Reconnaissance Orbiter (LRO) launched with the Lunar Orbiter Laser Altimeter (LOLA), an instrument that precisely measures the Moon's surface elevation. LOLA is recorded in Lunar polar tracks, making this data particularly sparse in the equatorial regions where NASA has large sets of orbital images captured over the last five decades. The coregistration of orbital images (often...
Successful approaches to the robot localization problem include particle filters, which estimate non-parametric localization belief distributions. Particle filters are successful at tracking a robot’s pose, although they fare poorly at determining the robot’s global pose. The global localization problem has been addressed for robots that sense unambiguous visual landmarks with sensor resetting, by...
In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have been numerous and successful, and we build...
Particle filters for mobile robot localization must balance computational requirements and accuracy of localization. Increasing the number of particles in a particle filter improves accuracy, but also increases the computational requirements. Hence, we investigate a different paradigm to better utilize particles than to increase their numbers. To this end, we introduce the Corrective Gradient Refinement...
Particle filters for mobile robot localization must balance computational requirements and accuracy of localization. Increasing the number of particles in a particle filter improves accuracy, but also increases the computational requirements. Hence, we investigate a different paradigm to better utilize particles than to increase their numbers. To this end, we introduce the Corrective Gradient Refinement...
Hybrid sensor networks consisting of both in-expensive static wireless sensors and highly capable mobile robots have the potential to monitor large environments at a low cost. To do so, an algorithm is needed to assign tasks to mobile robots which minimizes communication among the static sensors in order to extend the lifetime of the network. We present three algorithms to solve this task allocation...
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