A Method for Modifying Closed-Loop Motion Plans to Satisfy Unpredictable Dynamic Constraints at Runtime

In this paper; the problem of motion planning in environments with both known static obstacles and unpredictable dynamic constraints is considered. A methodology is introduced in which the motion plan for the static environment is modified on-line to accommodate the unpredictable constraints in such a way that the completeness properties of the original motion plan are preserved. At the heart of the approach is the idea that Navigation functions are indeed Lyapunov functions; and that the traditional method of forcing the robot to track the negative gradient of field is not the only input which stabilizes the system. This extra freedom in selecting the input is used to accommodate the dynamic constraints. A computational method for selecting the appropriate inputs is given. The method is used to solve two sample problems. The constraints in these cases are used to model collisions with other robots and, in the second example, a team of robots traveling in formation. Finally, some preliminary work on extending the approach to nonholonomic systems is presented

Maintaining Wireless Connectivity Constraints for Robot Swarms in the Presence of Obstacles

The swarm paradigm of multirobot cooperation relies on a distributed architecture, where each robot makes its own decisions based on locally available knowledge. But occasionally the swarm members may need to share information about their environment or actions through some type of ad hoc communication channel, such as a radio modem, infrared communication, or an optical connection. In all of these cases robust operation is best attained when the transmitter/receiver robot pair is (1) separated by less than some maximum distance (range constraint); and (2) not obstructed by large dense objects (line-of-sight constraint). Therefore to maintain a wireless link between two robots, it is desirable to simultaneously comply with these two spatial constraints. Given a swarm of point robots with specified initial and final configurations and a set of desired communication links consistent with the above criteria, we explore the problem of designing inputs to achieve the final configuration while preserving the desired links for the duration of the motion. Some interesting conclusions about the feasibility of the problem are offered. A potential field-based optimization algorithm is provided, along with a novel composition scheme, and its operation is demonstrated through both simulation and experimentation on a group of small robots

Computational Techniques for Analysis of Genetic Network Dynamics

In this paper we propose modeling and analysis techniques for genetic networks that provide biologists with insight into the dynamics of such systems. Central to our modeling approach is the framework of hybrid systems and our analysis tools are derived from formal analysis of such systems. Given a set of states characterizing a property of biological interest P, we present the Multi-Affine Rectangular Partition (MARP) algorithm for the construction of a set of infeasible states I that will never reach P and the Rapidly Exploring Random Forest of Trees (RRFT) algorithm for the construction of a set of feasible states F that will reach P. These techniques are scalable to high dimensions and can incorporate uncertainty (partial knowledge of kinetic parameters and state uncertainty). We apply these methods to understand the genetic interactions involved in the phenomenon of luminescence production in the marine bacterium V. fischeri

A Framework and Architecture for Multi-Robot Coordination

In this paper, we present a framework and the software architecture for the deployment of multiple autonomous robots in an unstructured and unknown environment with applications ranging from scouting and reconnaissance, to search and rescue and manipulation tasks. Our software framework provides the methodology and the tools that enable robots to exhibit deliberative and reactive behaviors in autonomous operation, to be reprogrammed by a human operator at run-time, and to learn and adapt to unstructured, dynamic environments and new tasks, while providing performance guarantees. We demonstrate the algorithms and software on an experimental testbed that involves a team of car-like robots using a single omnidirectional camera as a sensor without explicit use of odometry

Computer Law Institute

Materials from the Computer Law Institute held by UK/CLE in May 1999

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr