Corners Of Obstacles Research Articles

Ultrafast Euclidean Shortest Path Computation Using Hub Labeling

Finding shortest paths in a Euclidean plane containing polygonal obstacles is a well-studied problem motivated by a variety of real-world applications. The state-of-the-art algorithms require finding obstacle corners visible to the source and target, and need to consider potentially a large number of candidate paths. This adversely affects their query processing cost. We address these limitations by proposing a novel adaptation of hub labeling which is the state-of-the-art approach for shortest distance computation in road networks. Our experimental study conducted on the widely used benchmark maps shows that our approach is typically 1-2 orders of magnitude faster than two state-of-the-art algorithms.

Adapting hippocampus multi-scale place field distributions in cluttered environments optimizes spatial navigation and learning.

Extensive studies in rodents show that place cells in the hippocampus have firing patterns that are highly correlated with the animal's location in the environment and are organized in layers of increasing field sizes or scales along its dorsoventral axis. In this study, we use a spatial cognition model to show that different field sizes could be exploited to adapt the place cell representation to different environments according to their size and complexity. Specifically, we provide an in-depth analysis of how to distribute place cell fields according to the obstacles in cluttered environments to optimize learning time and path optimality during goal-oriented spatial navigation tasks. The analysis uses a reinforcement learning (RL) model that assumes that place cells allow encoding the state. While previous studies have suggested exploiting different field sizes to represent areas requiring different spatial resolutions, our work analyzes specific distributions that adapt the representation to the environment, activating larger fields in open areas and smaller fields near goals and subgoals (e.g., obstacle corners). In addition to assessing how the multi-scale representation may be exploited in spatial navigation tasks, our analysis and results suggest place cell representations that can impact the robotics field by reducing the total number of cells for path planning without compromising the quality of the paths learned.

A Hybrid Routing Approach Using Two Searching Layers

Abstract This paper considers SUB_GOALs by using basic A* algorithm and Subgoal Graphs in a hybrid approach to execute optimal route. SUB_GOALs identified with pre-searching from basic A* at break points and Subgoal Graphs at corners of obstacles are added to SUB_TABLE to expedite the final searching in the hybrid approach. Map to work on is divided to subregions with decision-making process by using line-of-sight to avoid redundant searching. In the final searching layer, all feasible SUB_GOALs gained from decision-making process in the same subregion are connected to find final solutions of routes. Solutions achieved in the divided subregions are evaluated and combined to discover the final optimal route. The proposed hybrid approach is applied to three different scenarios in various dimensions of maps. In these three scenarios, the shortest route without hitting obstacles is calculated as 46.67, 57.76 and 124.7 units, respectively, and compared with other search algorithms. Simulation results of route planning are demonstrated to exhibit the effectiveness of the proposed hybrid approach.

Evacuation through area with obstacle that can be stepped over: experimental study

This paper reports on a series of evacuation experiments exploring the impact of different obstacles on crowd dynamics. The experiments include three scenarios: evacuation without any obstacle (NO), evacuation with a bar-type obstacle in which the participants can choose to pass by or step over (CO), and evacuation with a bar-type obstacle in which the participants can only pass by (PO). The height of the obstacle and the distance between the obstacle and the exit in the CO cases are also taken into account. The evacuation times in the CO cases are basically longer than those in the PO cases. But a low CO obstacle very close to the exit can enhance the evacuation efficiency, compared to that of a PO obstacle. As the height of the CO obstacle increases, the pedestrian cluster around the exit separates into two clusters around the obstacle corners. In addition, the longer the distance between the CO obstacle and the exit, the fewer pedestrians prefer to step over the obstacle.

A novel methodology for determining sky blocking by obstacles viewed virtually from any location on site

This paper presents an innovative methodology for determining sky blocking by obstacles, when viewed virtually from any location on a site. These sky blockings are defined in the form of azimuth and altitude angles (or position angles) of exposed corners of obstacles around locations, proposed for solar installations at the site. To determine sky blockings, the surveyor does not need to be present at that height or location. Rather few measurements would be taken from two easily accessible points (preferably on ground) and then the results will be extrapolated so as to determine sky blockings from required height or location. Some other surveying parameters are also recorded which are discussed in details. Trigonometric relations are derived which aid in viewing the obstacle virtually from any other chosen point on site which may not necessarily lie in the same plane as of reference points. Steps for performing physical survey are also explained which only requires measuring few angles and lengths. The method is demonstrated with a case study for validation. Ultimately, this innovative approach extends the flexibility in employing already existing sun-path diagram based site analysis methods by allowing surveyor to evaluate angles without physically reaching the desired locations. Application of proposed methodology lies in performing site analysis for solar installations in urban areas where energy is largely consumed.

Speeding-Up Any-Angle Path-Planning on Grids

Simple Subgoal Graphs are constructed from grids by placing subgoals at the corners of obstacles and connecting them. They are analogous to visibility graphs for continuous terrain but have fewer edges and can be used to quickly find shortest paths on grids. The vertices of a Simple Subgoal Graph can be partitioned into different levels to create N-Level Subgoal Graphs, which can be used to find shortest paths on grids even more quickly by ignoring subgoals that are not relevant for the search, which significantly reduces the size of the graph being searched. Search using Two-Level Subgoal Graphs was a non-dominated entry in the Grid-Based Path Planning Competitions 2012 and 2013. In this paper, we take advantage of the similarities between Subgoal Graphs and visibility graphs to show that Subgoal Graphs can be used, with small modifications, to quickly find “any-angle” paths, thus extending their applicability. Any-angle paths are usually shorter and more realistic looking than grid paths since the movement along any-angle paths is not constrained to grid edges. Our algorithm has the advantage that it is a simple extension of searching Subgoal Graphs and is up to two orders of magnitude faster than Theta* and up to an order of magnitude faster than Block A* (using 5 × 5 blocks), two of the most well-known any-angle pathplanning algorithms, while still finding any-angle paths of comparable lengths.

Subgoal Graphs for Optimal Pathfinding in Eight-Neighbor Grids

Grids are often used to represent maps in video games. In this paper, we propose a method for preprocessing eightneighbor grids to generate subgoal graphs and show how subgoal graphs can be used to find shortest paths fast. We place subgoals at the corners of obstacles (similar to visibility graphs) and add those edges between subgoals that are necessary for finding shortest paths, while ensuring that each edge connects only subgoals that are easily reachable from one another. We describe a method for finding shortest paths by first finding high-level paths through subgoals and then shortest low-level paths between consecutive subgoals on the highlevel path. Our method was one of ten entries in the Grid-Based Path Planning Competition 2012. Among all optimal path planners, ours was the fastest to find complete paths and required the least amount of memory.

Numerical heat transfer in a rectangular channel with mounted obstacles on upper and lower walls

A numerical investigation of convective heat transfer between a fluid and three physical obstacles (blocks) mounted on the lower wall (2 blocks) and on the upper wall (1 block) of a rectangular channel was conducted. Laminar flow of the fluid circulating through the channel was assumed. The effect of the Reynolds number, block spacing and dimensions and solid to fluid thermal conductivity ratio were studied. A uniform heat flux through the blocks was assumed. The results showed that transition from steady to unsteady flows occurred at lower values of the Reynolds number when an obstacle is placed on the upper wall of the channel. The isotherms around the blocks were presented and the heat transfer evaluated through the Nusselt number. As expected, the results obtained showed that as the value of the Reynolds number was increased, the heat removed from the obstacles increased sensibly with a maximum heat removal around the obstacle corners. Moreover, the temperature difference between the three obstacles decreased as the Reynolds number was increased. Some disagreement in the results was observed when compared with those reported in the literature.

Evidence for the use of reflected self-generated seismic waves for spatial orientation in a blind subterranean mammal

Subterranean mammals like the blind mole-rat (Rodentia: Spalax ehrenbergi) are functionally blind and possess poor auditory sensitivity, limited to low-frequency sounds. Nevertheless, the mole-rat demonstrates extremely efficient ability to orient spatially. A previous field study has revealed that the mole-rat can assess the location, size and density of an underground obstacle, and accordingly excavates the most efficient bypass tunnel to detour around the obstacles. In the present study we used a multidisciplinary approach to examine the possibility that the mole-rat estimates the location and physical properties of underground obstacles using reflected self-generated seismic waves (seismic 'echolocation'). Our field observations revealed that all the monitored mole-rats produced low-frequency seismic waves (250-300 Hz) at intervals of 8+/-5 s (range: 1-13 s) between head drums while digging a bypass to detour an obstacle. Using a computerized simulation model we demonstrated that it is possible for the mole-rat to determine its distance from an obstacle boundary (open ditch or stone) by evaluating the amplitude (intensity) of the seismic wave reflected back to it from the obstacle interface. By evaluating the polarity of the reflected wave the mole-rat could distinguish between air space and solid obstacles. Further, the model showed that the diffracted waves from the obstacle's corners could give the mole-rat precise information on the obstacle size and its relative spatial position. In a behavioural experiment using a special T-maze setup, we tested whether the mole-rat can perceive seismic waves through the somatosensory system and localize the source. The results revealed that the mole-rat is able to detect low frequency seismic waves using only its paws, and in most cases the mole-rats determined accurately the direction of the vibratory source. In a histological examination of the glabrous skin of the mole-rat's paws we identified lamellate corpuscle mechanoreceptors that might be used to detect low frequency seismic waves. The combined findings from these different approaches lead us to suggest that a specialized seismic 'echolocation' system could be used by subterranean mammals to determine the most energy-conserving strategy with which to bypass an obstacle, as well as to estimate their distance from the surface, keeping their tunnels at the optimal depth.

Mobile robot localization based on Monte Carlo method and genetic algorithms

Mobile robot localization is one of the crucial problems as far as autonomous mobile robots are concerned. Among many proposed techniques, the Monte Carlo localization algorithm has been reported as an adequate approach with respect to the solution of problems involving pose estimation for mobile robots. This article presents a Monte Carlo-based localization algorithm coupled to a genetic algorithm, whose main function is to compensate for localization errors caused by deficiencies of the probabilistic models for sensing and acting considered in the standard Monte Carlo method. In the context of Mobile Robotics, those modelling problems are caused by misreadings from sonar sensors facing obstacle corners and edges.

Approximate motion planning and the complexity of the boundary of the union of simple geometric figures

We study rigid motions of a rectangle amidst polygonal obstacles. The best known algorithms for this problem have a running time of Ω(n 2), wheren is the number of obstacle corners. We introduce thetightness of a motion-planning problem as a measure of the difficulty of a planning problem in an intuitive sense and describe an algorithm with a running time ofO((a/b · 1/ɛcrit + 1)n(logn)2), wherea ≥b are the lengths of the sides of a rectangle and ɛcrit is the tightness of the problem. We show further that the complexity (= number of vertices) of the boundary ofn bow ties (see Figure 1) isO(n). Similar results for the union of other simple geometric figures such as triangles and wedges are also presented.

A new efficient motion-planning algorithm for a rod in two-dimensional polygonal space

We present here a new and efficient algorithm for planning collision-free motion of a line segment (a rod or a “ladder”) in two-dimensional space amidst polygonal obstacles. The algorithm uses a different approach than those used in previous motion-planning techniques, namely, it calculates the boundary of the (three-dimensional) space of free positions of the ladder, and then uses this boundary for determining the existence of required motions, and plans such motions whenever possible. The algorithm runs in timeO(K logn) =O(n 2 logn) wheren is the number of obstacle corners and whereK is the total number of pairs of obstacle walls or corners of distance less than or equal to the length of the ladder. The algorithm has thus the same complexity as the best previously known algorithm of Leven and Sharir [5], but if the obstacles are not too cluttered together it will run much more efficiently. The algorithm also serves as an initial demonstration of the viability of the technique it uses, which we expect to be useful in obtaining efficient motion-planning algorithms for other more complex robot systems.

An efficient and simple motion planning algorithm for a ladder amidst polygonal barriers

We present a relatively simple motion-planning algorithm for a line segment (a “ladder”) moving in 2-dimensional space amidst polygonal obstacles. The algorithm runs in time O( n 2log n), where n is the number of obstacle corners, and is shown to be close to optimal. The algorithm is an optimized variant of the decomposition technique of the configuration space of the ladder, due to Schwartz and Sharir ( Comm. Pure Appl. Math. 36 (1983), 345–398; Advan. Appl. Math. 4 (1983), 298–351; Robotics Res. 2(3) (1983), 46–75). The optimizing approach used in our algorithm may be exploited to improve the efficiency of existing motion-planning algorithms for other more complex robot systems.

Diffraction of Sound 1

THE interest of the subject which I propose to bring before A you this evening turns principally upon the connection or analogy between light and sound. It has been known for a very long time that sound is a vibration; and everyone here knows that light is a vibration also. The last piece of knowledge, however, was not arrived at so easily as the first; and one of the difficulties which retarded the acceptance of the view that light is a vibration was that in some respects the analogy between light and sound seemed to be less perfect than it should be. At the present time many of the students at our schools and universities can tell glibly all about it; yet this difficulty is one not to be despised, for it exercised a determining influence over the great mind of Newton. Newton, it would seem, definitely rejected the wave-theory of light on the ground that according to such a theory light would turn round the corners of obstacles, and so abolish shadows, in the way that sound is generally supposed to do. The fact that this difficulty seemed to Newton to be insuperable is, from the point of view of the advancement of science, very encouraging. The difficulty which stopped Newton two centuries ago is no difficulty now. It is well known that the question depends upon the relative wavelengths in the two cases. Light-shadows, are sharp under ordinary circumstances, because the wave-length of light is so small; sound-shadows are usually of a diffused character, because the wave-length of sound is so great. The gap between the two is enormc-us. I need hardly remind you that the wave-length of C in the middle of the musical scale is about 4 feet. The wave-length of the light with which we are usually concerned, the light towards the middle of the spectrum, is about the forty-thousandth of an inch. The result is that an obstacle which is immensely large for light may be very small for sound, and will therefore behave in a different manner.