10441616
Automatic Gait Optimization with Gaussian Process Regression
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function optimization procedures that suffer from three key drawbacks. Local optimization techniques are naturally plagued by local optima, make no use of the expensive gait evaluations once a local step is taken, and do not explicitly model noise in gait evaluation. These drawbacks increase the need for a large number of gait evaluations, making optimization slow, data inefficient, and manually intensive. We present a Bayesian approach based on Gaussian process regression that addresses all three drawbacks. It uses a global search strategy based on a posterior model inferred from all of the individual noisy evaluations. We demonstrate the technique on a quadruped robot, using it to optimize two different criteria: speed and smoothness. We show in both cases our technique requires dramatically fewer gait evaluations than state-of-the-art local gradient approaches.
7940350
Experimental results towards content-based sub-image retrieval
We are interested in the problem of sub-image retrieval (CBSIR), i.e., given a query image one must find the best candidate images that contain that query image. We use two kinds of image feature vectors: global color histograms and autocorrelograms and experimented with several distance measures for both feature vectors in our experimental system. After extensive experimentation we found that using autocorrelograms with the so-called S/sub 1/ distance measure yielded excellent results for sub-image retrieval with an acceptable processing overhead.
6023729
Accurately Choosing Execution Runs for Software Fault Localization
Software fault localization involves locating the exact cause of error for a “failing” execution run – a run which exhibits an unexpected behavior. Given such a failing run, fault localization often proceeds by comparing the failing run with a “successful” run, that is, a run which does not exhibit the unexpected behavior. One important issue here is the choice of the successful run for such a comparison. In this paper, we propose a control flow based difference metric for this purpose. The difference metric takes into account the sequence of statement instances (and not just the set of these instances) executed in the two runs, by locating branch instances with similar contexts but different outcomes in the failing and the successful runs. Given a failing run πf and a pool of successful runs S, we choose the successful run πs from S whose execution trace is closest to πf in terms of the difference metric. A bug report is then generated by returning the difference between πf and πs. We conduct detailed experiments to compare our approach with previously proposed difference metrics. In particular, we evaluate our approach in terms of (a) effectiveness of bug report for locating the bug, (b) size of bug report and (c) size of successful run pool required to make a decent choice of successful run.
47136995
Routing for symmetric FPGAs and FPICs
A new class of routing structures with fixed orthogonal wire segments and field programmable switches at the intersections of the wire segments is proposed. In comparison with the conventional two-dimensional field-programmable gate array (FPGA) routing structure, this class of routing structures has the advantage of using a smaller number of active programmable switches. An existing field-programmable interconnect chip (FPIC) routing structure can be included as a special case in our class of routing structures. Using a probabilistic model, we prove that complete routing can be achieved with a high degree of probability in a routing structure of this class in which the number of tracks in each channel approaches the lower bound asymptotically. We present a sequential routing algorithm based on the solution of the single net routing problem. We take into account the delay introduced by the active programmable switches on a routing path and formulate the single net routing problem as a node-weighted Steiner minimum tree (NWSMT) problem in a bipartite graph G. Since our single net routing problem is NP-complete, a polynomial time approximate algorithm is proposed. We prove that our single net routing algorithm produces an optimal solution for some special classes of bipartite graphs. In general, the solution obtained by our algorithm bas a performance bound of min{/spl Delta/(V/Z), |Z|-1}. Experimental results for several industrial circuits show a reduction of up to 41% in the number of active programmable switches when compared with corresponding results for the conventional FPGA routing structure.
39372956
An Inequality on Connected Domination Parameters
195837988
An optimal algorithm for floorplan area optimization
An optimal algorithm for the VLSI floorplan area optimization problem is presented. The algorithm is an extension of the technique described by L. Stockmeyer (Information and Control, vol.59, p.91-101, 1983). Experimental results indicate that this algorithm pruned a very large number of redundant implementations. In addition, since the algorithm basically exploits the geometric property of the topology of the given floorplan it does not need to depend on the polar dual graphs to calculate the longest paths. Consequently it is able to run more efficiently than the branch-and-bound algorithm.<<ETX>>
15147164
Balanced incomplete designs for 3D perceptual quality estimation
Many factors, such as the number of vertices and the resolution of texture, can affect the display quality of 3D objects. When the resources of a graphics system are not sufficient to render the ideal image, degradation is inevitable. It is therefore important to study how individual factors affect the overall quality, and how the degradation can be controlled given limited resources. The essential factors determining the display quality are reviewed and a 3D perceptual estimation method is described. One of the major concerns in designing perceptual experiments is the large number of evaluations to be performed by judges, which results in fatigue and errors in judgement. To reduce judging fatigue and increase reliability of evaluations we propose using a statistical approach, following the design of experiments technique of balanced incomplete block design (BIBD). We develop models following BIBD for perceptual experiments and validate our model with experimental results. Even though the BIBD framework for perceptual evaluations is described in the context of 3D quality estimation, the approach can be used in other perceptual evaluation scenarios as well.