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Theory of Graphs, American Mathematical Society, Providence, RI, 1962 43 E Lucas Recreations Mathematique, A Blanchard, Paris, 1892 44 G Tarry Le problem des labyrinthes Nouvelles Annales de Mathematiques 14:187 189, 1895 45 A Fraenkel Economic traversal of labyrinths Mathematics Magazine 44:12, 1970 46 A Fraenkel Economic traversal of labyrinths Mathematics Magazine 43:125 130, 1971 47 B Bullock, D Keirsey, J Mitchell, T Nussmeier, and D Tseng Autonomous vehicle control: An overview of the Hughes project In Proceedings of the IEEE Computer Society Conference Trends and Applications: Automating Intelligent Behavior, Gaithesburg, MD, May 1983 48 A M Thompson The navigation system of the JPL robot In Proceedings of 5th Joint International Conference on Arti cial Intelligence, Cambridge, MA, 1977 49 C Thorpe Path relaxation: Path planning for a mobile robot Technical report CMU-RI-TR-84-5, Carnegie-Mellon University, 1984 50 D Keirsey, E Koch, J McKisson, A Meystel, and J Mitchell.

One obvious t for high-level design techniques is that of state-machine creation. Remembering back to our rst course in logic design, we learned to design state machines by rst drawing a state-transition diagram and then translating this to HDL (or gates as the course may be) manually. The state-diagram representation is a natural abstraction that ts well with our existing design process. One feature of describing state machines in HDL is the vast number of valid state-machine encodings that are available to the designer. There are statemachine encodings that are optimal for compact designs and those that are well suited for high-speed designs. Many of the variations have to do with designer preference, but this also introduces the possibility of human error, not to mention software translation error when recognizing a state-machine description. Oftentimes a designer does not have the knowledge whether one state-machine encoding will be optimal for his or her implementation until after synthesis has been performed. Modifying the state-machine encoding is time consuming and is generally not related to the functionality of the state machine. It is true that most synthesis tools will recognize a state machine and recode it based on the physical design constraints, but a higher-level description that gives the synthesis tool the most exibility regarding the implementation details is, in general, an optimal approach. Take for example the following state machine that loads a multiplier and accumulator for a low-pass DSP function:

Algorithm for navigation of a mobile robot In Proceedings of the International Conference on Robotics, Atlanta, GA, 1984 51 R Chatila Path planning and environment learning in a mobile robot system In Proceedings European Conference on Arti cial Intelligence, Torsey, France, 1982 52 R Chattergy Some heuristics for the navigation of a robot International Journal of Robotics Research 4(1):59 66, 1985 53 J Crowley Navigation for an intelligent mobile robot IEEE Journal of Robotics and Automation RA-1(1):31 41, 1985 54 A Petrov and I Sirota Control of a robot manipulator with obstacle avoidance under little information about the environment In Proceedings of the VIII Congress of IFAC, Vol XIV, Kyoto, Japan, 1981 55 In Proceedings of the IEEE International Conference on Intelligent Robots and Systems, IROS 2003, Las Vegas, 2003..

56 V Lumelsky A comparative study on the path length performance of mazesearching and robot motion planning algorithms IEEE Transactions on Robotics and Automation, 7(1):57 66, 1991 57 W S Massey Algebraic Topology, Harcourt, Brace & World, New York, 1967 58 V Lumelsky and A Stepanov Path planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape Algorithmica 2:403 430, 1987 59 V Lumelsky Effect of kinematics on dynamic path planning for planar robot arms moving amidst unknown obstacles IEEE Journal of Robotics and Automation RA-3(3):207 223, 1987 60 A Sankaranarayanan and M Vidyasagar Path planning for moving a point object amidst unknown obstacles in a plane: The universal lower bound on the worst path lengths and a classi cation of algorithms In Proceedings of the IEEE International Conference on Robotics and Automation, Sacramento, CA, 1991 61 A Blake and A Yuille.

module shelflow( output reg output reg [23:0] output reg [23:0] output reg output reg [23:0] input input [23:0] input input [23:0] input input [23:0] multstart, multdat, multcoeff, clearaccum, U0, CLK, RESET, iData, // X[0] iWriteStrobe, // X[0] is valid iALow, iCLow, // coeffs for low pass filter multdone, accum);

What s up I asked I have a card for you He was really thinking hard about this one But I don t know if I can give it to you Was it a business card from the human resources people at Ernest Wellington Another contact Craig s mentor or friend He was hooking me up! Of course, I wanted to play it cool and not seem so anxious that I scared him off It s okay if you can t for right now, I lied to him I was probably willing to kill him right then and there for the card, but I knew that a homicide was going to look bad on my employment record, and probably affect my ability to get back to the office in time to trade again Well, he replied, Technically, I shouldn t give it to you right now So I won t.