Showing papers on "Bounding overwatch published in 2006"

On the Stability of the Passive Dynamics of Quadrupedal Running with a Bounding Gait

Abstract: This paper examines the passive dynamics of quadrupedal bounding. First, an unexpected difference between local and global behavior of the forward speed versus touchdown angle in the self-stabilized Spring Loaded Inverted Pendulum (SLIP) model is exposed and discussed. Next, the stability properties of a simplified sagittal plane model of our Scout II quadrupedal robot are investigated. Despite its simplicity, this model captures the targeted steady state behavior of Scout II without dependence on the fine details of the robot structure. Two variations of the bounding gait, which are observed experimentally in Scout II, are considered. Surprisingly, numerical return map studies reveal that passive generation of a large variety of cyclic bounding motion is possible. Most strikingly, local stability analysis shows that the dynamics of the open loop passive system alone can confer stability to the motion! These results can be used in developing a general control methodology for legged robots, resulting from the synthesis of feedforward and feedback models that take advantage of the mechanical system, and might explain the success of simple, open loop bounding controllers on our experimental robot.

On the Dynamics of Bounding and Extensions: Towards the Half-Bound and Gallop Gaits

Abstract: This paper examines how simple control laws stabilize complex running behaviors such as bounding. First, we discuss the unexpectedly different local and global forward speed versus touchdown angle relationships in the self-stabilized Spring Loaded Inverted Pendulum. Then we show that, even for a more complex energy conserving unactuated quadrupedal model, many bounding motions exist, which can be locally open loop stable! The success of simple bounding controllers motivated the use of similar control laws for asymmetric gaits resulting in the first experimental implementations of the half-bound and the rotary gallop on Scout II.

Lightweight Bounding Volumes for Ray Tracing

Abstract: This paper presents a memory-efficient auxiliary data structure for ray tracing called a lightweight bounding volume hierarchy, or LBVH. The new data structure reduces memory requirements in three ways: using implicit indexing, limited precision numbers, and a high branching factor. We show that LBVHs can be nearly as effective as standard bounding volumes in terms of speed while using significantly less memory. C++ source code for a ray tracer that implements LBVHs is provided online.

Bounding Gait in a Hybrid Wheeled-Leg Robot

Abstract: This paper discusses the first implementation of a dynamically stable bounding gait on a hybrid wheeled-leg robot. Design of the robot is reviewed and the controllers which allow this mode of mobility to occur are discussed. Experimental results demonstrating the key dynamic characteristics of the gait, including footfall patterns, are given. The hypothesis that varying leg takeoff angles can lead to regulation of forward speed of the bounding gait is presented and verified. In addition, comparisons are made between the bounding gait which uses active wheel control and bounding which uses passive mechanical blocking of the wheels.

Bounding Rational Analysis: Constraints on Asymptotic Performance

Abstract: Critical of mechanistic accounts of cognition, Anderson (1990) showed that a demonstration that cognition is optimally adapted to its purpose and environment can offer an explanation for its structure. Simon (1992), in contrast, emphasised that the study of an adaptive system is not a " logical study of optimization, " but an empirical study of the conditions that limit the approach to the optimum. In response, we sketch the requirements for an approach to explaining behaviour that emphasises explanations in terms of the optimal behaviour given not only descriptions of the objective and environment but also descriptions of the human cognitive architecture and knowledge. A central assumption of the proposal is that a theory explains behaviour if the optimal behaviour predicted by the theory shows substantial correspondence to asymptotic human performance.

Implicit bounding volumes and bounding volume hierarchies

Abstract: Computing and maintaining proximity information between objects are crucial tasks in modeling and simulating the world around us as in robotic motion planning, physics based simulation, molecular dynamics, etc. The information is important as objects in real life do not normally penetrate and most of the interactions between objects happen when they are near each other. Popular methods for answering proximity and collision queries use bounding volume hierarchies (BVHs). In these methods a bounding volume hierarchy is constructed for each object so that the object is captured in more and more details as one goes down the hierarchy. Bounding volume hierarchies allow one to determine quickly if two objects are not in close proximity. The further apart the objects are, the less traversal the methods have to do and thus the less work in determining the proximity between the objects. This dissertation presents results that show the power of implicit bounding volumes and implicit bounding volume hierarchies for proximity query and collision detection. The first part of the dissertation, we propose to use of zonotopes (Minkoswki sums of line segments) as bounding volumes. By defining the bounding volumes implicitly through generating segments, complicated shapes can be captured tightly with a small number of segments. Efficient algorithms for computing exact and approximate optimal bounding volumes, as well as algorithms to detect interference between zonotopes are provided. In the second part of this dissertation, we study ways to represent bounding volume hierarchies implicitly as combinatorial objects, making them stable when objects undergo large deformation. We rigourously analyze the performance of our data structures and algorithms, and obtain the first data structure for bounding volume hierarchies that is maintainable under motion and deformation. We also show that proximity structures such as (1 + e) well separated pair decompositions, (I + e)-spanners, approximate Voronoi diagrams, and approximate k-centers can be obtained from our bounding volume hierarchies, and these structures are also maintainable under motion and deformation.

Survey of Box-based Algorithms for Collision Detection

Abstract: Different algorithms for collision detections(CD)in virtual scene were surveyed.The principle and effectiveness of axis-aligned bounding boxes(AABB)method,oriented bounding box method(OBB),discrete orientation polytopes(k-DOP)method and Space-Time Bounding Boxes(STBB)method were discussed in detail.The results of analysis prove that the simpleness of bounding box is in contradiction with the compactness of wrapped object and the k-DOP method is between AABB method and OBB method in the effectiveness of CD.The main results are useful for designing virtual scene.

Model Checking of Continuous-Time Markov Chains by Closed-Form Bounding Distributions

Abstract: Continuous-time Markov chains (CTMCs) have been largely applied with combination of high-level model specification techniques as performance evaluation and dependability, reliability analysis models for computer and communication systems. These models can be complemented by probabilistic model checking formalisms based on temporal logic to specify the guarantees on the measures of interest. We consider in this paper Continuous Stochastic Logic (CSL) which lets to express real-time probabilistic properties on CTMCs. It has been shown that the CSL operators can be checked by means of transient or steady-state analysis of the underlying CTMC. Since models are checked to see if the considered measures are guaranteed or not, bounding techniques are useful in probabilistic model checking. We propose to apply Stochastic Comparison technique to construct bounding models having a special structure which provides closed-form solutions to compute both transient and steady-state distributions. We present an algorithm to provide rapid model checking by means of these closed-form bounding distributions. Obviously, bounding distributions may not let to decide if the underlying model meets the probability thresholds or not. However in the case where the model can be checked by the proposed method, we gain significantly in time and memory complexity.

Multidimensional segmentation based on adaptive bounding box and ellipsoid models

Abstract: A seed point is selected inside a structure that is to be segmented in image data. An adaptive model is defined around the seed point, and a preprocessing filter is applied only within the bounding region. A presegmentation of the preprocessed result is performed, and the bounding region is expanded if necessary to accommodate the presegmentation result. An adaptive model for post-processing may be used. The model is translated, rotated and scaled to find a best fit with the pre-segmented data.

Detecting Ellipses via Bounding Boxes

Abstract: A novel algorithm for ellipse detection based on bounding boxes is proposed in this paper. The bounding box is used in many different contexts in computer graphics as a complexity limiting device. For a perfect ellipse, the bounding box can be located by scanning an image and the corresponding geometric features can then be derived. The concept of bounding box is similar to that of the geometric symmetry approach. Instead of finding edges, we utilize a preprocessed binary image as the input to our algorithm. The search space of parameters is also condensed to a small area. Simulation results show the effectiveness of our approach.

Algorithms for bounding Folkman numbers

Abstract: For an undirected, simple graph G, we write G → (a1, . . . , ak) v (G → (a1, . . . , ak) ) if for every vertex (edge) k-coloring of G, a monochromatic Kai is forced in some color i ∈ {1, . . . , k}. The vertex (edge) Folkman number is defined as Fv(a1, . . . , ak; p) = min{|V (G)| : G→ (a1, . . . , ak; p) , Kp 6⊆ G} Fe(a1, . . . , ak; p) = min{|V (G)| : G→ (a1, . . . , ak; p) , Kp 6⊆ G} for p > max{a1, . . . , ak}. Folkman showed in 1970 that these numbers always exist for valid values of p. This thesis concerns the computation of a new result in Folkman number theory, namely that Fv(2, 2, 3; 4) = 14. Previously, the bounds stood at 10 ≤ Fv(2, 2, 3; 4) ≤ 14, proven by Nenov in 2000. To achieve this new result, specialized algorithms were executed on the computers of the Computer Science network in a distributed processing effort. We discuss the mathematics and algorithms used in the computation. We also discuss ongoing research into the computation of the value of Fe(3, 3; 4); the current bounds stand at 16 ≤ Fe(3, 3; 4) ≤ 3 × 10 . The upper bound on this number was once the subject of an Erdös prize—claimed by Spencer in 1988.

Multi-Objective Propagation in Constraint Programming

Abstract: Bounding constraints are used to bound the tolerance of solutions under certain undesirable features. Standard solvers propagate them one by one. Often times, it is easy to satisfy them independently, but difficult to satisfy them simultaneously. Therefore, the standard propagation methods fail. In this paper we propose a novel approach inspired in multi-objective optimization. We compute a multi-objective lower bound set that, if large enough, can be used to detect the inconsistency of the problem. Our experiments on two domains inspired in real-world problems show that propagation of additive bounding constraints using our approach is clearly superior than previous approaches.

A 3D Model Retrieval Based on Combinations of Partial Shape Descriptors

Abstract: Similarity retrieval techniques for 3D models have been intensively investigated the last few years. The purpose has been to improve precision of the similarity retrievals, and as a result various types of shape descriptors have been proposed. Several shape descriptors use the bounding box of a 3D model during a shape descriptor extraction process, and computation of the bounding box is important for accurately identifying shape descriptors. In our previous shape descriptor extraction approaches, only one bounding box was used for each 3D model. However, use of one bounding box is a very rough approximation of the shape for certain 3D models. When the bounding box becomes very sparse for certain targeted 3D models, the approach can not compute shape descriptors accurately. In this research, we have extended the shape descriptor computation technique by using a multiple number of bounding boxes. 3D models are decomposed into multiple parts, and multiple numbers of bounding boxes are used for each decomposed part. Shape descriptors are extracted from each decomposed 3D model part independently, and they are combined with weighted values based on the proportions of area size of each decomposed part. Our preliminary experiments showed that similarity retrievals results were improved for certain 3D models by using a combination of partial shape descriptors.

Bounding functions methods for fully nonlinear boundary value problems

Abstract: Using the bounding functions method and the theory of topological degree, this paper presents the existence criterion of solution for third-order BVP with nonlinear boundary conditions and extends the existing results.

A multi-step strategy for approximate similarity search in image databases

Abstract: Many strategies for similarity search in image databases assume a metric and quadratic form-based similarity model where an optimal lower bounding distance function exists for filtering. These strategies are mainly two-step, with the inital "filter" step based on a spatial or metric access method followed by a "refine" step employing expensive computation. Recent research on robust matching methods for computer vision has discovered that similarity models behind human visual judgment are inherently non-metric. When applying such models to similarity search in image databases, one has to address the problem of nonmetric distance functions that might to have an optimal lower bound for filtering. Here, we propose a novel three-step "prune-filter-refine" strategy for approximate similarity search on these models. First, the "prune" step adopts a spatial access method to roughly eliminate improbable matches via an adjustable distance threshold. Second, the "filter" step uses a quasi lower-bounding distance derived from the non-metric distance function of the similarity model. Third, the "refine" stage compares the query with the remaining candidates by a robust matching method for final ranking. Experimental results confirmed that the proposed strategy achieves more filtering than a two-step approach with close to no false drops in the final result.

On bounding the delay of a critical path

Abstract: Process variations cause different behavior of timing-dependent effects across different chips. In this work, we analyze one example of timing-dependent effects, cross-coupling capacitance, and the complex problem space created by considering coupling and process variations together. The delay of a critical path under these conditions is difficult to bound for design and test. We develop a methodology that analyzes this complex space by decomposing the problem space along three dimensions: the aggressor space, test space, and sample space. For design, we utilize an OBDD-based approach to prune the aggressor space based on logical constraints, which can be combined with a worst-case timing window simulator to prune based on both logical and timing constraints. After pruning, the reduced aggressor space can be used to derive a more accurate timing bound. Solving the problems in the test and sample spaces is postponed to the post-silicon stage, where we propose a test selection methodology for bounding the delay of every sample. This methodology is based on probability density estimation and has a tradeoff between the number of tests to apply and the tightness of the delay bound obtained. Experimental results based on benchmark examples are presented to show the effectiveness of the proposed methodology.

Orientation Diversity for an Autonomous Underwater Vehicle Cluster

Abstract: This paper presents a novel theory for the generation of vehicle heading sequences that simultaneously ensures orientation diversity both between vehicles and along a given vehicle's path, while at the same time bounding the cluster divergence, and translating the cluster. The theory is based on periodic sequences of polygonal paths. The paper presents the basic theory including performance functions for rating and ranking the "optimality" of different sequences. The paper also presents novel algorithms for generating "optimal" path sequences for any size cluster as well as simulation results of these algorithms.

Bounding transient and steady-state dependability measures through algorithmic stochastic comparison

Abstract: We are interested in bounding dependability measures like point and steady-state availability and reliability of systems modelled by very large Markov chains which are not numerically tractable. We suppose that the state space is divided into two classes, UP (system is operational) and DOWN states. The reliability at time t is defined as the probability that the system has always been operational between 0 and t. The point availability is the probability that the system is operational at time t, and the steady-state availability is the limit, if it exists, of this probability.

Bounding Strategies forScheduling on Identical Parallel Machines

Abstract: Weaddress theproblem ofminimizing makespan on identical parallel machines. We proposenew lower bounding strategies andheuristics forthis fundamental scheduling problem. Thelower bounds arebased on theso-called lifting procedure. In addition, twooptimization-based