Israel A. Wagner

Distributed covering by ant-robots using evaporating traces

We investigate the ability of a group of robots, that communicate by leaving traces, to perform the task of cleaning the floor of an un-mapped building, or any task that requires the traversal of an unknown region. More specifically, we consider robots which leave chemical odour traces that evaporate with time, and are able to evaluate the strength of smell at every point they reach, with some measurement error. Our abstract model is a decentralized multi-agent adaptive system with a shared memory, moving on a graph whose vertices are the floor-tiles. We describe three methods of covering a graph in a distributed fashion, using smell traces that gradually vanish with time, and show that they all result in eventual task completion, two of them in a time polynomial in the number of tiles. Our algorithms can complete the traversal of the graph even if some of the agents die or the graph changes during the execution, as long as the graph stays connected. Another advantage of our agent interaction processes is the ability of agents to use noisy information at the cost of longer cover time.

Gate-diffusion input (GDI): a power-efficient method for digital combinatorial circuits

Gate diffusion input (GDI) - a new technique of low-power digital combinatorial circuit design - is described. This technique allows reducing power consumption, propagation delay, and area of digital circuits while maintaining low complexity of logic design. Performance comparison with traditional CMOS and various pass-transistor logic design techniques is presented. The different methods are compared with respect to the layout area, number of devices, delay, and power dissipation. Issues like technology compatibility, top-down design, and precomputing synthesis are discussed, showing advantages and drawbacks of GDI compared to other methods. Several logic circuits have been implemented in various design styles. Their properties are discussed, simulation results are reported, and measurements of a test chip are presented.

Cooperative Cleaners: A Study in Ant Robotics

In the world of living creatures, simple-minded animals often cooperate to achieve common goals with amazing performance. One can consider this idea in the context of robotics, and suggest models for programming goal-oriented behavior into the members of a group of simple robots lacking global supervision. This can be done by controlling the local interactions between the robot agents, to have them jointly carry out a given mission. As a test case we analyze the problem of many simple robots cooperating to clean the dirty floor of a non-convex region in Z 2 , using the dirt on the floor as the main means of inter-robot communication.

A Distributed Ant Algorithm for\protect Efficiently Patrolling a Network

Abstract We consider the problem of patrolling—i.e. ongoing exploration of a network by a decentralized group of simple memoryless robotic agents. The model for the network is an undirected graph, and our goal, beyond complete exploration, is to achieve close to uniform frequency of traversal of the graph’s edges. A simple multi-agent exploration algorithm is presented and analyzed. It is shown that a single agent following this procedure enters, after a transient period, a periodic motion which is an extended Eulerian cycle, during which all edges are traversed an identical number of times. We further prove that if the network is Eulerian, a single agent goes into an Eulerian cycle within 2|E|D steps, |E| being the number of edges in the graph and D being its diameter. For a team of k agents, we show that after at most 2( 1 + 1/k) |E|D steps the numbers of edge visits in the network are balanced up to a factor of two. In addition, various aspects of the algorithm are demonstrated by simulations.

Efficiently searching a graph by a smell-oriented vertex process

Efficient graph search is a central issue in many aspects of AI. In most of existing work there is a distinction between the active “searcher”, which both executes the algorithm and holds the memory, and the passive “searched graph”, over which the searcher has no control at all. Large dynamic networks like the Internet, where the nodes are powerful computers and the links have narrow bandwidth and are heavily-loaded, call for a different paradigm, in which most of the burden of computing and memorizing is moved from the searching agent to the nodes of the network. In this paper we suggest a method for searching an undirected, connected graph using the Vertex-Ant-Walk method, where an a(ge)nt walks along the edges of a graph G, occasionally leaving “pheromone” traces at nodes, and using those traces to guide its exploration. We show that the ant can cover the graph within time O(nd), where n is the number of vertices and d the diameter of G. The use of traces achieves a trade-off between random and self-avoiding walks, as it dictates a lower priority for already-visited neighbors. Further properties of the suggested method are: (a) modularity: a group of searching agents, each applying the same protocol, can cooperate on a mission of covering a graph with minimal explicit communication between them; (b) possible convergence to a limit cycle: a Hamiltonian path in G (if one exists) is a possible limit cycle of the process.

MAC Versus PC: Determinism and Randomness as Complementary Approaches to Robotic Exploration of Continuous Unknown Domains

Three methods are described for exploring a continuous unknown planar region by a group of robots having limited sensors and no explicit communication. We formalize the problem, prove that its off-line version is NP-hard, and show a lower bound on the length of any solution. Then a deterministic mark and cover (MAC) algorithm is described for the on-line problem using short-lived navigational markers as a means of navigation and indirect communication. The convergence of the algorithm is proved, and its cover time is shown to be the asymptotically optimal O(A/a), where A is the total area and a is the area covered by the robot in a single step. The MAC algorithm is tested against an alternative randomized probabilistic covering (PC) method, which does not rely on sensors but is still able to cover an unknown region in an expected time that depends polynomially on the dimensions of the region. Both algorithms enable cooperation of several robots to achieve faster coverage. Finally, we show that the two methods can be combined to yield a third, hybrid algorithm with a better trade-off between performance and robustness.

Spatial openness as a practical metric for evaluating built-up environments

This paper reports on a primary metric tool developed in a collaboration between an architecture researcher and a computer science researcher. The development of this tool emerged from the concept that the spatial openness (SO)—the volume of free space measured from all possible observation points—is an important quality indicator of alternative spatial configurations within given constraints; this concept is based on the idea that the geometry and morphology of the built-up environment influence perception. Previous work showed that comparative SO measurements in alternative spatial configurations are correlated with the comparative perceived density, and in particular that a higher value of SO indicates a lower perceived density. We present a feasible 3D computational method for measuring SO and demonstrate its potential use in the design process. The SO metric is a step towards the development of quantitative comparative evaluation of building shapes and spatial configurations related to the 3D observation of open space.

Ants: agents on networks, trees, and subgraphs

Abstract Efficient exploration of large networks is a central issue in data mining and network maintenance applications. In most existing work there is a distinction between the active ‘searcher’ which both executes the algorithm and holds the memory and the passive ‘searched graph’ over which the searcher has no control at all. Large dynamic networks like the Internet, where the nodes are powerful computers and the links have narrow bandwidth and are heavily-loaded, call for a different paradigm, in which a noncentralized group of one or more lightweight autonomous agents traverse the network in a completely distributed and parallelizable way. Potential advantages of such a paradigm would be fault tolerance against network and agent failures, and reduced load on the busy nodes due to the small amount of memory and computing resources required by the agent in each node. Algorithms for network covering based on this paradigm could be used in today’s Internet as a support for data mining and network control algorithms. Recently, a vertex ant walk ( VAW ) method has been suggested [I.A. Wagner, M. Lindenbaum, A.M. Bruckstein, Ann. Math. Artificial Intelligence 24 (1998) 211–223] for searching an undirected, connected graph by an a(ge)nt that walks along the edges of the graph, occasionally leaving ‘pheromone’ traces at nodes, and using those traces to guide its exploration. It was shown there that the ant can cover a static graph within time nd , where n is the number of vertices and d the diameter of the graph. In this work we further investigate the performance of the VAW method on dynamic graphs, where edges may appear or disappear during the search process. In particular we prove that (a) if a certain spanning subgraph S is stable during the period of covering, then the VAW method is guaranteed to cover the graph within time nd s , where d s is the diameter of S , and (b) if a failure occurs on each edge with probability p , then the expected cover time is bounded from above by nd(( log Δ / log (1/p))+((1+p)/(1−p))) , where Δ is the maximum vertex degree in the graph. We also show that (c) if G is a static tree then it is covered within time 2 n .

Efficient cooperative search of smart targets using uav swarms1

This work examines the Cooperative Hunters problem, where a swarm of unmanned air vehicles (UAVs) is used for searching one or more “evading targets,” which are moving in a predefined area while trying to avoid a detection by the swarm. By arranging themselves into efficient geometric flight configurations, the UAVs optimize their integrated sensing capabilities, enabling the search of a maximal territory.

On-chip interconnect-aware design and modeling methodology based on high bandwidth transmission line devices

This paper expands the on-chip interconnect-aware methodology for high-speed analog and mixed signal design, presented in D. Goren et al. (2002), into a wider class of designs, including dense layout CMOS design. The proposed solution employs a set of parameterized on-chip transmission line (T-line) devices for the critical interconnects, which is expanded to include coplanar structures while considering the silicon substrate effect. The generalized methodology contains treatment of the crossing line effects at the various design stages, including two way interactions between the post layout extraction tool and the T-line devices. The T-line device models are passive by construction, easily migratable among design environments, and allow for both time and frequency domain simulations. These models are verified by S-parameter measurements up to 110GHz, as well as by EM solver results. It is experimentally shown that the effect of properly designed discontinuities is negligible in most practical cases. The basic on-chip T-line methodology is being used extensively for numerous high-speed designs.