Supporting Memorization and Problem Solving with Spatial Information Presentations in Virtual Environments

While it has been suggested that immersive virtual environments could provide benefits for educational applications, few studies have formally evaluated how the enhanced perceptual displays of such systems might improve learning. Using simplified memorization and problem-solving tasks as representative approximations of more advanced types of learning, we are investigating the effects of providing supplemental spatial information on the performance of learning-based activities within virtual environments. We performed two experiments to investigate whether users can take advantage of a spatial information presentation to improve performance on cognitive processing activities. In both experiments, information was presented either directly in front of the participant or wrapped around the participant along the walls of a surround display. In our first experiment, we found that the spatial presentation caused better performance on a memorization and recall task. To investigate whether the advantages of spatial information presentation extend beyond memorization to higher level cognitive activities, our second experiment employed a puzzle-like task that required critical thinking using the presented information. The results indicate that no performance improvements or mental workload reductions were gained from the spatial presentation method compared to a non-spatial layout for our problem-solving task. The results of these two experiments suggest that supplemental spatial information can support performance improvements for cognitive processing and learning-based activities, but its effectiveness is dependent on the nature of the task and a meaningful use of space

Object tracking with stereo vision

A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking

Hand-Eye Calibration of Robonaut

NASA's Human Space Flight program depends heavily on Extra-Vehicular Activities (EVA's) performed by human astronauts. EVA is a high risk environment that requires extensive training and ground support. In collaboration with the Defense Advanced Research Projects Agency (DARPA), NASA is conducting a ground development project to produce a robotic astronaut's assistant, called Robonaut, that could help reduce human EVA time and workload. The project described in this paper designed and implemented a hand-eye calibration scheme for Robonaut, Unit A. The intent of this calibration scheme is to improve hand-eye coordination of the robot. The basic approach is to use kinematic and stereo vision measurements, namely the joint angles self-reported by the right arm and 3-D positions of a calibration fixture as measured by vision, to estimate the transformation from Robonaut's base coordinate system to its hand coordinate system and to its vision coordinate system. Two methods of gathering data sets have been developed, along with software to support each. In the first, the system observes the robotic arm and neck angles as the robot is operated under external control, and measures the 3-D position of a calibration fixture using Robonaut's stereo cameras, and logs these data. In the second, the system drives the arm and neck through a set of pre-recorded configurations, and data are again logged. Two variants of the calibration scheme have been developed. The full calibration scheme is a batch procedure that estimates all relevant kinematic parameters of the arm and neck of the robot The daily calibration scheme estimates only joint offsets for each rotational joint on the arm and neck, which are assumed to change from day to day. The schemes have been designed to be automatic and easy to use so that the robot can be fully recalibrated when needed such as after repair, upgrade, etc, and can be partially recalibrated after each power cycle. The scheme has been implemented on Robonaut Unit A and has been shown to reduce mismatch between kinematically derived positions and visually derived positions from a mean of 13.75cm using the previous calibration to means of 1.85cm using a full calibration and 2.02cm using a suboptimal but faster daily calibration. This improved calibration has already enabled the robot to more accurately reach for and grasp objects that it sees within its workspace. The system has been used to support an autonomous wrench-grasping experiment and significantly improved the workspace positioning of the hand based on visually derived wrench position. estimates

Getting Lost While Trying to Follow the Money: Special Education Finance in Charter Schools

Tracking the special education dollars that support services for students with disabilities attending public schools is complicated; attempting to track the funds to autonomous public charter schools is even more so. Public schools -- traditional and charter alike -- receive their operating revenues from three primary sources: local property taxes, state per-pupil allocations, and federal categorical-aid programs. The aggregate resources available to provide services to students with disabilities in public schools is a function of both 1) funding available to public schools generally, and 2) funding designated to support special education and related services in particular.Understanding how dollars flow to charter schools requires consideration of multiple and overlapping federal, state, and local district formulas and policies, and understanding how state policymakers have retrofitted these policies and procedures to include autonomous charter school