Integrating environmental awareness and sustainability issues in a beginning agronomy course

Agriculture in the United States in a science- based, highly technical field that has signifi­ cant impact on society and the larger ecosys­ tem, both nationally and internationally. As new technologies and challenges continually emerge, educational and research efforts in agriculture have been and will continue to be key to the success of agronomic systems. At the same time, human labor in U.S. agriculture has decreased rapidly; less than 2% of the population is directly involved in agricultural production. Rapid technological change and declining farm populations suggest that we are becoming a nation largely illiterate in agricul­ tural and sustainable production issues

Humanoid Mobile Manipulation Using Controller Refinement

An important class of mobile manipulation problems are move-to-grasp problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. In this paper, it is proposed that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and characterizes this type of solution. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box. In a series of tests, it is shown that a refining sequence of controllers decreases variance in robot configuration relative to the sample box until a successful grasp has been achieved

GREAT/SOFIA atmospheric calibration

The GREAT observations need frequency-selective calibration across the passband for the residual atmospheric opacity at flight altitude. At these altitudes the atmospheric opacity has both narrow and broad spectral features. To determine the atmospheric transmission at high spectral resolution, GREAT compares the observed atmospheric emission with atmospheric model predictions, and therefore depends on the validity of the atmospheric models. We discusse the problems identified in this comparison with respect to the observed data and the models, and describe the strategy used to calibrate the science data from GREAT/SOFIA during the first observing periods.Comment: 14 pages, 4 figure