We present in detail some of the challenges in developing reusable robotic software. We base that on our experience in developing the CLARAty robotics software, which is a generic object-oriented framework used for the integration of new algorithms in the areas of motion control, vision, manipulation, locomotion, navigation, localization, planning and execution. CLARAty was adapted to a number of heterogeneous robots with different mechanisms and hardware control architectures. In this paper, we also describe how we addressed some of these challenges in the development of the CLARAty software.

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To command a rover to go to a location of scientific interest on a remote planet, the rover must be capable of reliably tracking the target designated by a scientist from about ten rover lengths away. The rover must maintain lock on the target while traversing rough terrain and avoiding obstacles without the need for communication with Earth. Among the challenges of tracking targets from a rover are the large changes in the appearance and shape of the selected target as the rover approaches it, the limited frame rate at which images can he acquired and processed, and the sudden changes in camera pointing as the rover goes over rocky ternin. We have investigated various techniques for combining 2D and 3D information in order to increase the reliability of visually tracking targets under Mars like conditions. We will present the approaches that we have examined on simulated data and tested onboard the Rocky 8 rover in the JPL Mars Yard and the K9 rover in the ARC Marscape. These techniques include results for 2D trackers, ICP, visual odomew, and 2D/3D trackers.

This paper presents the development, validation, and deployment of the visual target tracking capability onto the Mars Exploration Rover (MER) mission. Visual target tracking enables targeted driving, in which the rover approaches a designated target in a closed visual feedback loop, increasing the target position accuracy by an order of magnitude and resulting in fewer ground-in-the-loop cycles. As a result of an extensive validation, we developed a reliable normalized cross-correlation visual tracker. To enable tracking with the limited computational resources of a planetary rover, the tracker uses the vehicle motion • Journal of Field Robotics-2009estimation to scale and roll the template image, compensating for large image changes between rover steps. The validation showed that a designated target can be reliably tracked within several pixels or a few centimeters of accuracy over a 10-m traverse using a rover step size of 10% of the target distance in any direction. It also showed that the target is not required to have conspicuous features and can be selected anywhere on natural rock surfaces excluding rock boundary and shadowed regions. The tracker was successfully executed on the Opportunity rover near Victoria Crater on four distinct runs, including a single-sol instrument placement. We present the flight experiment data of the tracking performance and execution time. C 2009 Wiley Periodicals, Inc.

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