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56 records · Page 4

Autonomous Rock Tracking and Acquisition from a Mars Rover

Future Mars exploration missions will perform two types of experiments: science instrument placement for close-up measurement, and sample acquisition for return to Earth. In this paper we describe algorithms we developed for these tasks, and demonstrate them in field experiments using a self-contained Mars Rover prototype, the Rocky 7 rover. Our algorithms perform visual servoing on an elevation map instead of image features, because the latter are subject to abrupt scale changes during the approach. 'This allows us to compensate for the poor odometry that results from motion on loose terrain. We demonstrate the successful grasp of a 5 cm long rock over 1m away using 103-degree field-of-view stereo cameras, and placement of a flexible mast on a rock outcropping over 5m away using 43 degree FOV stereo cameras.

Maimone, Mark W.

On-board Absolute Localization Based on Orbital Imagery for a Future Mars Science Helicopter

Future Mars Rotorcraft require advanced navigationcapabilities to enable all terrain access over long distance flightsthat are executed fully autonomously. A critical component toenable precision navigation during long traverses is the abilityto perform on-board absolute localization to eliminate drift inposition estimates of the on-board odometry algorithm. Inthis paper, we present an approach for on-board map-basedlocalization to provide global reference position based on orbitalor aerial image maps. Our approach builds on a vision-basedlocalization method to localize against a map derived fromHiRISE image products – an ortho-projected image (orthoimage) and a corresponding digital elevation map. The mapis pre-computed using a feature-based approach. Features arestored with their 3D world coordinates, and a descriptor to codethe local image intensity information in the vicinity of the featurelocation. An on-board matching algorithm uses this informationto match visual features in a query image acquired during flight,guided by a pose prior from the on-board range-visual-inertialstate estimator (Range-VIO). Valid matches are then used bya perspective-n-point (PnP) algorithm to estimate the absolutepose of the vehicle in a global frame. We demonstrate andevaluate our approach on simulated data, and data from UASflights.

Balaram, J. Bob