Obstacles In Space Research Articles

Fatigue crack growth behaviour in titanium aluminides

Fatigue crack growth behaviour of several titanium aluminides has been examined. With increase in Al content from 13 to 50 at.%, microstructures change from (α + β) to ( α 2 + β) to ( α 2 + γ) and finally to γ where α 2 is Ti 3Al and γ is TiAl. The exact microstructure for a given alloy depends on the composition, presence of ternary elements that stabilize β, such as Nb, and heat treatment. The degrees of slip planarity and brittleness increase with increase in Al content as one proceeds from α to α 2 to equiatomic α. In addition, there is an increase in the propensity for faceted mode of crack growth with an increase in the degree of slip planarity. Fatigue threshold for a faceted crack growth depends on grain size or obstacle spacing. Hence crack growth rates can vary significantly for a given alloy depending on the microstructural scaling parameters, namely, equiaxed grain size or inter-obstacle spacing for Widmanstatten precipitates with basket-weave or lamellar structure. The load ratio effects have been analysed using the two parametric approach developed by the authors, and it is shown that the results can be explained without invoking an extraneous factor, namely crack closure.

Experimental investigations of crack trapping in brittle heterogeneous solids

Abstract Over the past two decades many mechanisms of toughening have been considered for brittle solids. Some of the most prominent ones, applicable to either monolithic materials or fiber-reinforced composites, include deformation-induced local transformations, microcracking, crack trapping, crack bridging, and fiber pull-out. Few, if any, of these have been studied in the past in a manner which permitted evaluation of the effects of individual mechanisms in the absence of other interacting mechanisms. Here, we present an experimental study of toughening by the process of crack trapping by second-phase particles (spheres and fibers) of such toughness that make them impenetrable by probing cracks, forcing the cracks to bow around the obstacles with increasing applied load. The model fracture specimens employed here were wedge-loaded double cantilever beams, cast of a brittle epoxy, containing macroscopic (3 mm diameter) inclusions of Nylon or polycarbonate, having elastic properties similar to the matrix. The tests were performed at −60°C to achieve controlled, stable crack propagation. Images of the crack fronts, advancing at velocities of about 10−4m/s, were recorded with good resolution, providing a continuous record of crack-front shapes during the evolution of the crack-trapping process — from the initial pinning configuration through the transition to crack-flank bridging. Remarkable agreement between these images and crack-front shapes predicted by the numerical simulation of Bower and Ortiz is demonstrated. A parametric approach was adopted to study the influence of obstacle spacing, surface adhesion, and thermally induced residual stresses upon the observed crack-front behavior and enhanced stress intensity required to propagate the cracks past these obstacles. Analysis of the quantitative data has demonstrated that in brittle matrices containing particle volume fractions of approximately 0.2, toughness enhancement by over a factor of 2, relative to neat matrix values, may be achieved through the crack-trapping mechanism alone, provided that a high level of adhesion can be maintained between the matrix and the tough reinforcing particles.

Shortest paths in the plane with polygonal obstacles

We present a practical algorithm for finding minimum-length paths between points in the Euclidean plane with (not necessarily convex) polygonal obstacles. Prior to this work, the best known algorithm for finding the shortest path between two points in the plane required Ω(n 2 log n) time and O (n 2 ) space, where n denotes the number of obstacle edges. Assuming that a triangulation or a Voronoi diagram for the obstacle space is provided with the input (if is not, either one can be precomputed in O ( n log n) time), we present an O(kn) time algorithm, where k denotes the number of “islands” (connected components) in the obstacle space. The algorithm uses only O(n) space and, given a source point s , produces an O(n) size data structure such that the distance between s and any other point x in the plane ( x ) is not necessarily an obstacle vertex or a point on an obstacle edge) can be computed in O (1) time. The algorithm can also be used to compute shortest paths for the movement of a disk (so that optimal movement for arbitrary objects can be computed to the accuracy of enclosing them with the smallest possible disk).

Artificial Neural Networks for Control of Autonomous Mobile Robots

The service robot is the future research subject in robotics. One of the basic operations of the service robot is the autonomous freely moving ability. In this paper the path finding problem and collision avoidance for an autonomous mobile robot will be investigated. At first the path finding problem of autonomous mobile robots in a two dimensional space among stationary obstacles is investigated. For the path finding problem Kohonen’s self-organising mapping will be applied. After path finding collision avoidance with moving obstacles in the work space using artificial neural networks will also be investigated.

Real-time robot path planning using the potential function method

An important problem in robotics is path planning, whose goal is to find a collision free path among obstacles in the work space. Most algorithms which have been developed to solve this problem are based on a mapping of the given problem into a finite state space which always resulted in a problem which can be solved by computer but has a high computational complexity. Previously developed algorithms which worked with continuous space were relatively unsophisticated. In a previous paper by the authors, an algorithm for collision avoidance was developed. This algorithm will now be incorporated into the potential function method for planning a collision free path.

Collision-Free Path Planning of Articulated Manipulators

A method is presented to efficiently compute a collision free path for manipulators with polyhedral links moving among polyhedral obstacles. The method is based on an analytical representation of the boundaries of configuration space obstacles (CSOB), obtained by modeling the contacts between manipulator links and obstacle as higher kinematic pairs. The contact conditions and manipulator kinematics are expressed in terms of homogeneous transformations, providing analytic relations between the joint angles and the contact variables. The set of joint angles associated with permissible contact variables forms the boundary of the CSOB. Using these analytical relations, the free space is efficiently divided into free-cells. Each contiguous set of free-cells is then represented by a connected graph that is of polynomial complexity in the number of geometric features of the obstacles and links. The shortest collision-free path on the graph is found using a best-first search. Examples are presented which demonstrate the method for a two link planar manipulator.

Theory of grain boundary motion in the presence of mobile particles

A theory of grain boundary motion in the presence of mobile particles is put forward. It is shown that the boundary-particle-interaction leads to a hysteresis in the velocity-driving relationship. The extent of the hysteresis depends on particle mobility, which is very sensitive to particle size. The effect of particles is discussed for planar and curved boundaries as well as volume particle distributions. The theory accounts for a smaller limiting grain size during grain growth than predicted by Zener drag. The concept can be generalized to include all kinds of mobile obstacles for boundary migration. In such cases not the distribution of obstacle spacing rather the distribution of obstacle mobilities will control microstructure evolution.

Determination of Allowable Manipulator Link Shapes; and Task, Installation, and Obstacle Spaces Using the Monte Carlo Method

The Monte Carlo method is used to solve a number of manipulator link shape design, task space, and obstacle placement problems. The shape of links of manipulators that are to operate within geometrically specified enclosures are determined. Within the enclosure, one or several obstacles may be present. For a specified operating environment, the spaces within which a given manipulator may be installed in order to perform the required tasks are identified. For a given enclosure, the allowable task spaces, and regions within which obstacles may be placed are mapped. By defining weighted distributions for the task and/or obstacle spaces, weighted allowable link shapes, and task and obstacle spaces are determined. The information can be used for optimal link shape synthesis, and for optimal task, obstacle, and manipulator placement purposes. The developed methods are very simple, numeric in nature, and readily implemented on computer. Several examples are presented.

Central Limit Theorem for a Random Walk with Random Obstacles in $\mathrm{R}^d$

A random walk with obstacles in $\mathbf{R}^d, d \geq 2$, is considered. A probability measure is put on a space of obstacles, giving a random walk with random obstacles. A central limit theorem is then proven for this process when the obstacles are distributed by a Gibbs state with sufficiently low activity. The same problem is treated for a tagged particle of an infinite hard core particle system.

スタンフォード型マニピュレータの障害物回避動作計画のための関節変数空間における物体のソリッドモデル表現法

On the problem of robot path planning using a configuration space approach, since boundaries of obstacles in the configuration space are very complex, it is difficult to construct those boundaries by analytic methods. Therefore, most of the approach to find a safe path are using search strategies, for examples, the configuration space is devided into cells and interferences are checked in each cell. But for those search strategies, it is difficult to determine the existence of the safe paths. This paper describes the method that represents the obstacles as a CSG/B-Reps dual solid model in the configuration space, by deriving the boundaries of obstacles in the configuration space in an analytical way. Using that solid model, an existence of the safe paths is determined, and if so, one of the safe paths is also generated.

Ｃｏｎｆｉｇｕｒａｔｉｏｎ空間における障害物記述に関する考察

For motion planning of a manipurator, the use of a configuration space is highly efficient. Algorithms of the collision-free planning in static environments have been proposed in many papers. The efficiency of the algorithms depends on the description of obstacles in a configuration space. In general, the complexity of a configuration space map exponentially increases with the number of joints. Therefore, building the configuration space map is a time-consuming process, and the collision-free path can not be searched in real time. In this paper, we illustrate mathematical properties of a new kind of configuration space and propose an approach to parameterizing an obstacle in the configuration space. A spherical obstacle in a work space is transformed into a characteristic subspace in the configuration space. Therefore, we can approximate parameters of a sphere as a set of geometric entities. The transformation of a complex work space into the configuration space is described in terms of integrating the transformation of each element of a set of spheres. A collision-free path in a dynamic environment is found by using a Penalty-Function-Method. The Penalty-Function is modified according to the factors of the velocity along axes in a polar coordinates system.

Path planning and the topology of configuration space

This work considers the path planning problem for planar revolute manipulators operating in a workspace of polygonal obstacles. This problem is solved by determining the topological characteristics of obstacles in configuration space, thereby determining where feasible paths can be found. A collision-free path is then calculated by using the mathematical description of the boundaries of only those configuration space obstacles with which collisions are possible. The key to this technique is a simple test for determining whether two disjoint obstacles are connected in configuration space. This test allows the path planner to restrict its calculations to regions in which collision-free paths are guaranteed a priori, thus avoiding unnecessary computations and resulting in an efficient implementation. Typical timing results for environments consisting of four polyhedral obstacles comprising a total of 27 vertices are of the order of 22 ms on a SPARC-IPC workstation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Obstacle avoidance in path planning using intersection constraint search

An important problem in robotics is to determine an obstacle avoidance control strategy which transfers the system along a collision free path among obstacles in the work space. Most algorithms which have been developed to solve this problem are based on a mapping of the given problem into a finite state which always resulted in a problem which can be solved by a computer, but has high computational complexity. Certain previously developed algorithms worked with continuous problem space, these algorithms were referred to as continuum algorithms and were relatively unsophisticated when compared to the continuous algorithms. This observation has served as a motivation for the research reported in this paper, in which it is desired to provide continuous space algorithms with a more rigorous theoretical base. The main result of this work is the development of a real-valued function, Ω, which characterizes the proximal relationship of two non-point convex bodies. This function is different from similar functions reported on elsewhere in that it also provides useful information when the sets (bodies) under consideration intersect. In this paper, the need for such a function is established, and certain computationally useful properties of the developed function are demonstrated.

Automated Computer-Aided Layout Planning for Robot Workcells

Abstract This text presents an approach for planning robot workcells in three dimensions fully automatically. This automation is possible by a complete layout planning process inside the configuration space. To reach a sufficient shop floor layout in a short time, the cartesian configuration space and fast obstacle transformation routines are employed. An optimization algorithm minimizes the length of all collision free paths required for the performance of the workcell task. A final check by a graphical workcell task simulation, whether the layout is valid or not, is no longer required. This new planning approach enhances the conventional layout planning process and reduces the amount of necessary user interaction.

Interactive graphics simulation with multi-level collision algorithm

Abstract An interactive, realistic computer graphics simulation package for robotic manipulators has been developed. Three PUMA robot manipulators and two existing robotic workcells have been implemented as specific applications. Interaction with the program is possible through user-friendly pop-up menus, information-display fields, and a unique on-screen teach pendant simulation. An interpreter for the robotic programming language VALII has been incorporated to interface with the graphics interface. The interpreter features a program-line trace mode to ease detection of logical errors in the control program. A multilevel collision-detection algorithm has been developed and implemented. The response time of the algorithm is a function of the proximity of the modelled manipulator to obstacles in the work space. It corresponds to the actual operation of the real robotic workcell.

Velocity potential approach to path planning for avoiding moving obstacles

This paper describes the theory and an experiment of a velocity potential approach to path planning and avoiding moving obstacles for an autonomous mobile robot by use of the Laplace potential. This new navigation function for path planning is feasible for guiding a mobile robot avoiding arbitrarily moving obstacles and reaching the goal in real time. The essential feature of the navigation function comes from the introduction of fluid flow dynamics into the path planning. The experiment is conducted to verify the effectiveness of the navigation function for obstacle avoidance in a real world. Two examples of the experiment are presented; first, the avoidance of a moving obstacle in parallel line-bounded space, and second, the avoidance of one moving obstacle and another standing obstacle. The robot can reach the goal after successfully avoiding the obstacles in these cases.

Real-Time Configuration Space Transforms for Obstacle Avoidance

A method is presented for computation of obstacle bound aries in configuration space, with particular emphasis on time efficiency. Properties of configuration space transfor mations are presented in general, and these properties are invoked in algorithms that result in highly efficient com putations. The approach depends on the definition of a set of primitives, which are themselves efficiently trans formed and may be combined logically to construct more complex transformations. The concepts are illustrated with both computed and empirically obtained configura tion space obstacles in two and three dimensions. Perfor mance data for real-time transformations are reported.

A new algorithm for shortest paths among obstacles in the plane

We introduce a new algorithm for computing Euclidean shortest paths in the plane in the presence of polygonal obstacles. In particular, for a given start points, we build a planar subdivision (ashortest path map) that supports efficient queries for shortest paths froms to any destination pointt. The worst-case time complexity of our algorithm isO(kn log2n), wheren is the number of vertices describing the polygonal obstacles, andk is a parameter we call the “illumination depth” of the obstacle space. Our algorithm usesO(n) space, avoiding the possibly quadratic space complexity of methods that rely on visibility graphs. The quantityk is frequently significantly smaller thann, especially in some of the cases in which the visibility graph has quadratic size. In particular,k is bounded above by the number of different obstacles that touch any shortest path froms.

A Unified Methodology for Motion Planning with Uncertainty for 2D and 3D Two-Link Robot Arm Manipulators

Most of the work on robot path planning revolves around two basic models: the model with complete information (often called the "Piano Mover's Problem") and the model with in complete information (called here the "South Pole Search Problem'). The approach of dynamic path planning intro duced in Lumelsky and Stepanov (1987) and Lumelsky (1987) is based on the latter model and produces nonheuristic (provable) algorithms for simple robot arm manipulators operating in an environment with unknown obstacles of arbi trary shapes. The algorithms assume local on-line input information coming from the arm sensors. Unfortunately, the existing techniques require that each kinematic configuration be considered separately, which results in different algo rithms for different kinematics. In this paper, a unified meth odology is presented for designing dynamic path planning algorithms for two- and three-dimensional two-link arm manipulators. The approach is independent of the specifics of the kinematic configuration and imposes no constraints on the shape of the arm links or obstacles in the environment. The methodology exploits some important topological char acteristics of the configuration space. However, no explicit computation of obstacles in the configuration space ever takes place, which results in fast real-time algorithms.

Real-time robot motion planning using rasterizing computer graphics hardware

We present a real-time robot motion planner that is fast and complete to a resolution. The technique is guaranteed to find a path if one exists at the resolution, and all paths returned are safe. The planner can handle any polyhedral geometry of robot and obstacles, including disjoint and highly concave unions of polyhedra.The planner uses standard graphics hardware to rasterize configuration space obstacles into a series of bitmap slices, and then uses dynamic programming to create a navigation function (a discrete vector-valued function) and to calculate paths in this rasterized space. The motion paths which the planner produces are minimal with respect to an L 1 (Manhattan) distance metric that includes rotation as well as translation.Several examples are shown illustrating the competence of the planner at generating planar rotational and translational plans for complex two and three dimensional robots. Dynamic motion sequences, including complicated and non-obvious backtracking solutions, can be executed in real time.