Certainty grids for mobile robots

A numerical representation of uncertain and incomplete sensor knowledge called Certainty Grids has been used successfully in several mobile robot control programs, and has proven itself to be a powerful and efficient unifying solution for sensor fusion, motion planning, landmark identification, and many other central problems. Researchers propose to build a software framework running on processors onboard the new Uranus mobile robot that will maintain a probabilistic, geometric map of the robot's surroundings as it moves. The certainty grid representation will allow this map to be incrementally updated in a uniform way from various sources including sonar, stereo vision, proximity and contact sensors. The approach can correctly model the fuzziness of each reading, while at the same time combining multiple measurements to produce sharper map features, and it can deal correctly with uncertainties in the robot's motion. The map will be used by planning programs to choose clear paths, identify locations (by correlating maps), identify well-known and insufficiently sensed terrain, and perhaps identify objects by shape. The certainty grid representation can be extended in the same dimension and used to detect and track moving objects

Moon-tracking orbits using motorized tethers for continuous earth–moon payload exchanges

For human colonization of the moon to become reality, an efficient and regular means of exchanging resources between the Earth and the moon must be established. One possibility is to pass and receive payloads at regular intervals between a symmetrically laden motorized momentum-exchange tether orbiting about Earth and a second orbiting about the moon. There are significant challenges associated with this method, among the greatest of which is the development of a system that incorporates the complex motion of the moon into its operational architecture in addition to conducting these exchanges on a per-lunar-orbit basis. One way of achieving this is to use a motorized tether orbiting Earth and tracking the nodes of the moon’s orbit to allow payload exchanges to be undertaken periodically with the arrival of the moon at either of these nodes. Tracking these nodes is achieved by arranging the tether to orbit Earth with a critical inclination, thus rendering its argument of perigee stationary in addition to using the precession effects resulting from an oblate Earth. Using this in conjunction with pre-emptive adjustments to its angle of right ascension, the tether will periodically realign itself with these nodes simultaneously with the arrival of the moon

Electrical properties of CdTe near the melting point

A new experimental setup for the investigation of electrical conductivity (σ) in liquid and solid CdTe was built for a better understanding of the properties near the melting point (MP). The temperature dependence of σ was studied, within the interval 1,050-1,130°C, at defined Cd-partial pressures 1.3-1.6 atm, with special attention to the liquid-solid phase transition. We found that the degree of supercooling decreases with increasing Cd overpressure and reaches the lowest value at 1.6 atm without change of the melting temperature during heating

Conceptual spatial representations for indoor mobile robots

We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of typical indoor environments. Following findings in cognitive psychology, our model is composed of layers representing maps at different levels of abstraction. The complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. The system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. Finally, we discuss the capabilities of the integrated system

The Incremental Garbage Collection of Processes

Key Words and Phrases: garbage collection, multiprocessing systems, processor scheduling. "lazy evaluation, "eager" evaluation. CR Categories: 3.60, 3.80, 4.13, 4.22, 4.32. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522. This paper was presented at the AI*PL Conference at Rochester, N.Y. in August, 1977.This paper investigates some problems associated with an argument evaluation order that we call "future" order, which is different from both call-by-name and call-by-value. In call-by-future, each formal parameter of a function is bound to a separate process (called a "future") dedicated to the evaluation of the corresponding argument. This mechanism allows the fully parallel evaluation of arguments to a function, and has been shown to augment the expressive power of a language. We discuss an approach to a problem that arises in this context: futures which were thought to be relevant when they were created become irrelevant through being ignored in the body of the expression where they were bound. The problem of irrelevant processes also appears in multiprocessing problem-solving systems which start several processors working on the same problem but with different methods, and return with the solution which finishes first. This parallel method strategy has the drawback that the processes which are investigating the losing methods must be identified, stopped, and re-assigned to more useful tasks. The solution we propose is that of garbage collection. We propose that the goal structure of the solution plan be explicitly represented in memory as part of the graph memory (like Lisp's heap) so that a garbage collection algorithm can discover which processes are performing useful work, and which can be recycled for a new task. An incremental algorithm for the unified garbage collection of storage and processes is described.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc