Boundary Of Obstacle Research Articles

Experience Learning From Basic Patterns for Efficient Robot Navigation in Indoor Environments

In this paper we propose a machine learning technique for real-time robot path planning for an autonomous robot in a planar environment with obstacles where the robot possess no a priori map of its environment. Our main insight in this paper is that a robot’s path planning times can be significantly reduced if it can refer to previous maneuvers it used to avoid obstacles during earlier missions, and adapt that information to avoid obstacles during its current navigation. We propose an online path planning algorithm called LearnerRRT that utilizes a pattern matching technique called Sample Consensus Initial Alignment (SAC-IA) in combination with an experience-based learning technique to adapt obstacle boundary patterns encountered in previous environments to the current scenario followed by corresponding adaptations in the obstacle-avoidance paths. Our proposed algorithm LearnerRRT works as a learning-based reactive path planning technique which enables robots to improve their overall path planning performance by locally improving maneuvers around commonly encountered obstacle patterns by accessing previously accumulated environmental information. We have conducted several experiments in simulations and hardware to verify the performance of the LearnerRRT algorithm and compared it with a state-of-the-art sampling-based planner. LearnerRRT on average takes approximately 10% of the planning time and 14% of the total time taken by the sampling-based planner to solve the same navigation task based on simulation results and takes only 33% of the planning time, 46% of total time and 95% of total distance compared to the sampling-based planner based on our hardware results.

Comparing methods for merging redundant line segments in maps

Abstract Map building of indoor environments is considered a basic building block for autonomous mobile robots, enabling, among others, self-localization and efficient path planning. While the mainstream approach stores maps as occupancy grids of regular cells, some works have advocated for the use of maps composed of line segments to represent the boundary of obstacles, leveraging on their more compact size. In order to limit both the growth of the corresponding data structures and the effort in processing these maps, a number of methods have been proposed for merging together redundant line segments that represent the same portion of the environment. In this paper, we experimentally compare some of the most significant methods for merging line segments in maps by applying them to publicly available data sets. At the end, we propose some guidelines to choose the appropriate method.

Generation of spiral waves pinned to obstacles in a simulated excitable system

Pinning phenomena emerge in many dynamical systems. They are found to stabilize extreme conditions such as superconductivity and super fluidity. The dynamics of pinned spiral waves, whose tips trace the boundary of obstacles, also play an important role in the human health. In heart, such pinned waves cause longer tachycardia. In this article, we present two methods for generating pinned spiral waves in a simulated excitable system. In method A, an obstacle is set in the system prior to an ignition of a spiral wave. This method may be suitable only for the case of large obstacles since it often fails when used for small obstacles. In method B, a spiral wave is generated before an obstacle is placed at the spiral tip. With this method, a pinned spiral wave is always obtained, regardless the obstacle size. We demonstrate that after a transient interval the dynamics of the pinned spiral waves generated by the methods A and B are identical. The initiation of pinned spiral waves in both two- and three-dimensional systems is illustrated.

Animating Wall-Bounded Turbulent Smoke via Filament-Mesh Particle-Particle Method.

Turbulent vortices in smoke flows are crucial for a visually interesting appearance. Unfortunately, it is challenging to efficiently simulate these appealing effects in the framework of vortex filament methods. The vortex filaments in grids scheme allows to efficiently generate turbulent smoke with macroscopic vortical structures, but suffers from the projection-related dissipation, and thus the small-scale vortical structures under grid resolution are hard to capture. In addition, this scheme cannot be applied in wall-bounded turbulent smoke simulation, which requires efficiently handling smoke-obstacle interaction and creating vorticity at the obstacle boundary. To tackle above issues, we propose an effective filament-mesh particle-particle (FMPP) method for fast wall-bounded turbulent smoke simulation with ample details. The Filament-Mesh component approximates the smooth long-range interactions by splatting vortex filaments on grid, solving the Poisson problem with a fast solver, and then interpolating back to smoke particles. The Particle-Particle component introduces smoothed particle hydrodynamics (SPH) turbulence model for particles in the same grid, where interactions between particles cannot be properly captured under grid resolution. Then, we sample the surface of obstacles with boundary particles, allowing the interaction between smoke and obstacle being treated as pressure forces in SPH. Besides, the vortex formation region is defined at the back of obstacles, providing smoke particles flowing by the separation particles with a vorticity force to simulate the subsequent vortex shedding phenomenon. The proposed approach can synthesize the lost small-scale vortical structures and also achieve the smoke-obstacle interaction with vortex shedding at obstacle boundaries in a lightweight manner. The experimental results demonstrate that our FMPP method can achieve more appealing visual effects than vortex filaments in grids scheme by efficiently simulating more vivid thin turbulent features.

B-Theta*: an Efficient Online Coverage Algorithm for Autonomous Cleaning Robots

We propose a novel approach to deal with the online complete-coverage task of cleaning robots in unknown workspaces with arbitrarily-shaped obstacles. Our approach is based on the boustrophedon motions, the boundary-following motions, and the Theta* algorithm known as B-Theta*. Under control of B-Theta*, the robot performs a single boustrophedon motion to cover an unvisited region. While performing the boustrophedon motion, if the robot encounters an obstacle with a boundary that has not yet been covered, it switches to the boundary mode to cover portions along the obstacle boundary, and then continues the boustrophedon motion until it detects an ending point. To move to an unvisited region, the robot detects backtracking points based on its accumulated knowledge, and applies an intelligent backtracking mechanism thanks to the proposed Theta* for multi-goals in order to reach the next starting point. Complete coverage is achieved when no starting point exists for a new boustrophedon motion. Computer simulations and experiments on real workspaces show that our proposed B-Theta* is efficient for the complete-coverage task of cleaning robots.

Research and verification for parabolic equation method of radio wave propagation in obstacle environment

In recent years, the two-way parabolic equation method (2WPE) has been widely utilized for studying the tropospheric ground-wave propagation under the irregular terrain. This algorithm can deal with the influences of the irregular terrain characteristic and the different electromagnetic parameters of the surface structure on wave propagation. However, there are still some defects in 2WPE method. Firstly, the method considers the irregular terrain and obstacles as a whole, so it cannot deal with the situation where the medium parameters of obstacles and the ground are different. Secondly, its calculation precision is limited with the inclination of the undulating terrain: if there are obstacles the upper bound of the inclination is easily broken through. Therefore, in this paper, a novel two-way parabolic equation method is proposed for analyzing the radio wave propagation in obstacle environment. According to the principle of domain decomposition, the obstacle zones are divided into two domains in the new algorithm, and the two subdomains are calculated, respectively. Meanwhile, in order to avoid the calculation error caused by the abrupt truncation of the obstacle zone, the field at the upper boundary of obstacles is modified to ensure the continuity of tangential field. To further improve the accuracy of the new algorithm, according to the historical transmission paths, we exactly retrieve the phases of each forward and backward wave, especially when stepping in and out of the obstacles. Furthermore, the method of moment (MoM) is used to verify the calculation accuracy of the new algorithm in obstacle environment. Although the accuracy of the MoM is very high, it also requires a great deal of calculation resources: it can only be employed to compute the fields in short distance. To overcome the difficulty, we use the image principle in the obstacle environment and do not subdivide the ground into segments; therefore the verification accuracy can be improved. On this basis, to unify the source setting of the new algorithm and the MoM, the equivalent source model is used to set the initial field. Finally, through numerical experiments, the simulation results of both methods agree very well, so the effectiveness of the boundary correction and the phase correction which are presented in this paper are both verified. The accuracy and superiority of the new algorithm in obstacle environment are also demonstrated. To sum up, the novel two-way parabolic equation method can be used to accurately calculate the field of the space in the obstacle environment, and lays the foundation for the field calculation of radio wave propagation in real environment.

Numerical solutions for handling systems of obstacle boundary value problems using the RPS method

Numerical solutions for handling systems of obstacle boundary value problems using the RPS method

Scattering theory of walking droplets in the presence of obstacles

We aim to describe a droplet bouncing on a vibrating bath using a simple and highly versatile model inspired from quantum mechanics. Close to the Faraday instability, a long-lived surface wave is created at each bounce, which serves as a pilot wave for the droplet. This leads to so called walking droplets or walkers. Since the seminal experiment by Couder et al (2006 Phys. Rev. Lett. 97 154101) there have been many attempts to accurately reproduce the experimental results.We propose to describe the trajectories of a walker using a Green function approach. The Green function is related to the Helmholtz equation with Neumann boundary conditions on the obstacle(s) and outgoing boundary conditions at infinity. For a single-slit geometry our model is exactly solvable and reproduces some general features observed experimentally. It stands for a promising candidate to account for the presence of arbitrary boundaries in the walker’s dynamics.

Optimization Using Boundary LookupJump Point Search

Cache-based path-finding algorithms lose much of their advantage in dynamic environments where fast online search algorithms are required. Jump point search (JPS) is such a fast algorithm. It works by eliminating most map nodes from evaluation during path expansion. Boundary lookup jump point search (BL–JPS) is a modification that improves the speed of JPS. BL–JPS records the positions of obstacle boundaries and uses these via direct lookup to eliminate much of the iteration involved in searching for jump points in the JPS algorithm. Two sets of experiments are presented, demonstrating the effects of BL–JPS in both static and dynamic environments. The effects of different approaches to cache rebuilding for JPS+ in dynamic environments are also evaluated. Results show that BL–JPS is generally much faster than JPS. It is slower than JPS+ in static environments, but in dynamic environments, BL–JPS outperforms JPS+ for a single search. When multiple paths are searched, the effects of cache rebuilding gradually dominate the effects of search speed, resulting in JPS+ again becoming faster. However, combining JPS+ with BL–JPS provides a very fast path-finding algorithm (BL–JPS+) that outperforms JPS+ over a range of map types and numbers of paths searched.

Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments

This paper presents a novel reactive collision avoidance method for mobile robots moving in dense and cluttered environments. The proposed method, entitled Tangential Gap flow (TGF), simplifies the navigation problem using a divide and conquer strategy inspired by the well-known Nearness-Diagram Navigation (ND) techniques. At each control cycle, the TGF extracts free openings surrounding the robot and identifies the suitable heading which makes the best progress towards the goal. This heading is then adjusted to avoid the risk of collision with nearby obstacles based on two concepts namely, tangential and gap flow navigation. The tangential navigation steers the robot parallel to the boundary of the closest obstacle while still emphasizing the progress towards the goal. The gap flow navigation safely and smoothly drives the robot towards the free area in between obstacles that lead to the target. The resultant trajectory is faster, shorter and less-oscillatory when compared to the ND methods. Furthermore, identifying the avoidance maneuver is extended to consider all nearby obstacle points and generate an avoidance rule applicable for all obstacle configurations. Consequently, a smoother yet much more stable behavior is achieved. The stability of the motion controller, that guides the robot towards the desired goal, is proved in the Lyapunov sense. Experimental results including a performance evaluation in very dense and complex environments demonstrate the power of the proposed approach. Additionally, a discussion and comparison with existing Nearness-Diagram Navigation variants is presented.

On the boundary layer structure near a highly permeable porous interface

The method of matched asymptotic expansions is used to study the canonical problem of steady laminar flow through a narrow two-dimensional channel blocked by a tight-fitting finite-length highly permeable porous obstacle. We investigate the behaviour of the local flow close to the interface between the single-phase and porous regions (governed by the incompressible Navier–Stokes and Darcy flow equations, respectively). We solve for the flow in these inner regions in the limits of low and high Reynolds number, facilitating an understanding of the nature of the transition from Poiseuille to plug to Poiseuille flow in each of these limits. Significant analytical progress is made in the high Reynolds number limit, and we explore in detail the rich boundary layer structure that occurs. We derive general results for the interfacial stress and for the conditions that couple the flow in the outer regions away from the interface. We consider the three-dimensional generalization to unsteady laminar flow through and around a tight-fitting highly permeable cylindrical porous obstacle within a Hele-Shaw cell. For the high Reynolds number limit, we give the coupling conditions and interfacial stress in terms of the outer flow variables, allowing information from a nonlinear three-dimensional problem to be obtained by solving a linear two-dimensional problem. Finally, we illustrate the utility of our analysis by considering the specific example of time-dependent forced far-field flow in a Hele-Shaw cell containing a porous cylinder with a circular cross-section. We determine the internal stress within the porous obstacle, which is key for tissue engineering applications, and the interfacial stress on the boundary of the porous obstacle, which has applications to biofilm erosion. In the high Reynolds number limit, we demonstrate that the fluid inertia can result in the cylinder experiencing a time-independent net force, even when the far-field forcing is periodic with zero mean.

A CIRCULAR-CYLINDRICAL FLUX-ROPE ANALYTICAL MODEL FOR MAGNETIC CLOUDS

ABSTRACT We present an analytical model to describe magnetic flux-rope topologies. When these structures are observed embedded in Interplanetary Coronal Mass Ejections (ICMEs) with a depressed proton temperature, they are called Magnetic Clouds (MCs). Our model extends the circular-cylindrical concept of Hidalgo et al. by introducing a general form for the radial dependence of the current density. This generalization provides information on the force distribution inside the flux rope in addition to the usual parameters of MC geometrical information and orientation. The generalized model provides flexibility for implementation in 3D MHD simulations. Here, we evaluate its performance in the reconstruction of MCs in in situ observations. Four Earth-directed ICME events, observed by the Wind spacecraft, are used to validate the technique. The events are selected from the ICME Wind list with the magnetic obstacle boundaries chosen consistently with the magnetic field and plasma in situ observations and with a new parameter (EPP, the Electron Pitch angle distribution Parameter) which quantifies the bidirectionally of the plasma electrons. The goodness of the fit is evaluated with a single correlation parameter to enable comparative analysis of the events. In general, at first glance, the model fits the selected events very well. However, a detailed analysis of events with signatures of significant compression indicates the need to explore geometries other than the circular-cylindrical. An extension of our current modeling framework to account for such non-circular CMEs will be presented in a forthcoming publication.

Multiple wave scattering by submerged obstacles in an infinite channel of finite depth. I. Streamlines

A finite number of rigid bodies of finite extent are submerged and kept fixed in an infinite, homogeneous layer of finite depth of an inviscid fluid of constant density. The layer is bounded from above by a free surface and from below by a horizontal impermeable bottom. An incident harmonic wave of given frequency propagating in the fluid layer is partially reflected by the obstacles, while part is transmitted after multiple scattering. The problem is to determine the resulting motion of the fluid in the frame of the linearized theory. A finite Fourier transform technique is used to this end, in combination with the methods of separation of variables, fundamental solutions and boundary collocation. This yields different expressions for the solution in different parts of the flow domain, each of which depends on a system of orthogonal functions. The obtained solution exhibits smoothness at any order in the fluid domain. It satisfies rigorously the field equation and all the boundary conditions, with the exception of the condition at the obstacle boundaries which is satisfied pointwise by boundary collocation. The method deals invariably with any finite number of obstacles, and its accuracy is clearly defined. Numerical applications with one and two circular obstacles are presented and the effects of the level of submergence are discussed. Plots are provided for the resulting system of streamlines.

Adaptive Region Boosting method with biased entropy for path planning in changing environment

Path planning in changing environments with difficult regions, such as narrow passages and obstacle boundaries, creates significant challenges. As the obstacles in W-space move frequently, the crowd degree of C-space changes accordingly. Therefore, in order to dynamically improve the sampling quality, it is appreciated for a planner to rapidly approximate the crowd degree of different parts of the C-space, and boost sample densities with them based on their difficulty levels. In this paper, a novel approach called Adaptive Region Boosting (ARB) is proposed to increase the sampling density for difficult areas with different strategies. What's more, a new criterion, called biased entropy, is proposed to evaluate the difficult degree of a region. The new criterion takes into account both temporal and spatial information of a specific C-space region, in order to make a thorough assessment to a local area. Three groups of experiments are conducted based on a dual-manipulator system with 12 DoFs. Experimental results indicate that ARB effectively improves the success rate and outperforms all the other related methods in various dynamical scenarios.

Exponential mixing properties for time inhomogeneous diffusion processes with killing

We consider an elliptic and time-inhomogeneous diffusion process with time-periodic coefficients evolving in a bounded domain of $\mathbb{R}^d$ with a smooth boundary. The process is killed when it hits the boundary of the domain (hard killing) or after an exponential time (soft killing) associated with some bounded rate function. The branching particle interpretation of the non absorbed diffusion again behaves as a set of interacting particles evolving in an absorbing medium. Between absorption times, the particles evolve independently one from each other according to the diffusion semigroup; when a particle is absorbed, another selected particle splits into two offsprings. This article is concerned with the stability properties of these non absorbed processes. Under some classical ellipticity properties on the diffusion process and some mild regularity properties of the hard obstacle boundaries, we prove an uniform exponential strong mixing property of the process conditioned to not be killed. We also provide uniform estimates w.r.t. the time horizon for the interacting particle interpretation of these non-absorbed processes, yielding what seems to be the first result of this type for this class of diffusion processes evolving in soft and hard obstacles, both in homogeneous and non-homogeneous time settings.

Surface turbulence for particle-based liquid simulations

We present a method to increase the apparent resolution of particle-based liquid simulations. Our method first outputs a dense, temporally coherent, regularized point set from a coarse particle-based liquid simulation. We then apply a surface-only Lagrangian wave simulation to this high-resolution point set. We develop novel methods for seeding and simulating waves over surface points, and use them to generate high-resolution details. We avoid error-prone surface mesh processing, and robustly propagate waves without the need for explicit connectivity information. Our seeding strategy combines a robust curvature evaluation with multiple bands of seeding oscillators, injects waves with arbitrarily fine-scale structures, and properly handles obstacle boundaries. We generate detailed fluid surfaces from coarse simulations as an independent post-process that can be applied to most particle-based fluid solvers.

Elimination of a spiral wave pinned at an obstacle by a train of plane waves: Effect of diffusion between obstacles and surrounding media.

In excitable media such as cardiac tissue and Belousov-Zhabotinsky reaction medium, spiral waves tend to anchor (pin) to local heterogeneities. In general, such pinned waves are difficult to eliminate and may progress to spatio-temporal chaos. Heterogeneities can be classified as either the absence or presence of diffusive interaction with the surrounding medium. In this study, we investigated the difference in the unpinning of spiral waves from obstacles with and without diffusive interaction, and found a profound difference. The pacing period required for unpinning at fixed obstacle size is larger in case of diffusive obstacles. Further, we deduced a generic theoretical framework that can predict the minimal unpinning period. Our results explain the difference in pacing periods between for the obstacles with and without diffusive interaction, and the difference is interpreted in terms of the local decrease of spiral wave velocity close to the obstacle boundary caused in the case of diffusive interaction.

전방 모노카메라 기반 장애물 검출 기술

This paper presents a new forward-viewing mono-camera based obstacle detection algorithm for mobile robots. The proposed method extracts the coarse location of an obstacle in an image using inverse perspective mapping technique from sequential images. In the next step, graph-cut based image labeling is conducted for estimating the exact obstacle boundary. The graph-cut based labeling algorithm labels the image pixels as either obstacle or floor as the final outcome. Experiments are performed to verify the obstacle detection performance of the developed algorithm in several examples, including a book, box, towel, and flower pot. The low illumination condition, low color contrast between floor and obstacle, and floor pattern cases are also tested.

Why the high-frequency inverse scattering by topological sensitivity may work.

This study deciphers the topological sensitivity (TS) as a tool for the reconstruction and characterization of impenetrable anomalies in the high-frequency regime. It is assumed that the anomaly is simply connected and convex, and that the measurements of the scattered field are of the far-field type. In this setting, the formula for TS-which quantifies the perturbation of a cost functional due to a point-like impenetrable scatterer-is expressed as a pair of nested surface integrals: one taken over the boundary of a hidden obstacle, and the other over the measurement surface. Using multipole expansion, the latter integral is reduced to a set of antilinear forms featuring Green's function and its gradient. The remaining expression is distilled by evaluating the scattered field on the surface of an obstacle via Kirchhoff approximation, and pursuing an asymptotic expansion of the resulting Fourier integral. In this way, the TS is found to survive upon three asymptotic lynchpins, namely (i) the near-boundary approximation for sampling points close to the 'exposed' surface of an obstacle; (ii) uniform expansions synthesizing the diffraction catastrophes for sampling points near caustic surfaces, lines and points; and (iii) stationary phase approximation. Within the framework of catastrophe theory, it is shown that, in the case of the full source aperture, the TS is asymptotically dominated by the (explicit) near-boundary term-which explains the previously reported reconstruction capabilities of this class of indicator functionals. The analysis further shows that, when the (Dirichlet or Neumann) character of an anomaly is unknown beforehand, the latter can be effectively exposed by assuming point-like Dirichlet perturbation and considering the sign of the leading term inside the reconstruction.

Critical velocity for vortex shedding in a Bose-Einstein condensate

We present measurements of the critical velocity for vortex shedding in a highly oblate Bose-Einstein condensate with a moving repulsive Gaussian laser beam. As a function of the barrier height $V_0$, the critical velocity $v_c$ shows a dip structure having a minimum at $V_0 \approx \mu $, where $\mu$ is the chemical potential of the condensate. At fixed $V_0\approx 7\mu$, we observe that the ratio of $v_c$ to the speed of sound $c_s$ monotonically increases for decreasing $\sigma/\xi$, where $\sigma$ is the beam width and $\xi$ is the condensate healing length. The measured upper bound for $v_c/c_s$ is about 0.4, which is in good agreement with theoretical predictions for a two-dimensional superflow past a circular cylinder. We explain our results with the density reduction effect of the soft boundary of the Gaussian obstacle, based on the local Landau criterion for superfluidity.