Obstacles In Space Research Articles

111 三次元空間における任意形状障害物を回避する目標経路の設計法(OS2-2 制御工学と機械システムの接点2,OS2 制御工学と機械システムの接点)

111 三次元空間における任意形状障害物を回避する目標経路の設計法(OS2-2 制御工学と機械システムの接点2,OS2 制御工学と機械システムの接点)

Physiological Intracellular Crowdedness is Defined by the Perimeter-to-Area Ratio of Sub-Cellular Compartments

The intracellular environment is known to be a crowded and inhomogeneous space. Such an in vivo environment differs from a well-diluted, homogeneous environment for biochemical reactions. However, the effects of both crowdedness and the inhomogeneity of environment on the behavior of a mobile particle have not yet been investigated sufficiently. As described in this paper, we constructed artificial reaction spaces with fractal models, which are assumed to be non-reactive solid obstacles in a reaction space with crevices that function as operating ranges for mobile particles threading the space. Because of the homogeneity of the structures of artificial reaction spaces, the models succeeded in reproducing the physiological fractal dimension of solid structures with a smaller number of non-reactive obstacles than in the physiological condition. This incomplete compatibility was mitigated when we chose a suitable condition of a perimeter-to-area ratio of the operating range to our model. Our results also show that a simulation space is partitioned into convenient reaction compartments as an in vivo environment with the exact amount of solid structures estimated from TEM images. The characteristics of these compartments engender larger mean square displacement of a mobile particle than that of particles in smaller compartments. Subsequently, the particles start to show confined particle-like behavior. These results are compatible with our previously presented results, which predicted that a physiological environment would produce quick response and slow exhaustion reactions.

2A1-B05 6関節遠隔操作ロボットの手先位置制御における冗長自由度温存による障害物適応(動作計画と制御の新展開)

The paper is concerned with execution of endpoint task in robotic teleoperation in the case that a part of telerobot's body interacts with an obstacle in telerobot's working space. Recently, without any force sensing the simultaneous realization of an endpoint task and adaptation to external forces acting on a part of body of a multi-joint robot has been presented. It is based on preserving redundant degrees of freedom of a robotic system during operation. By applying the idea to a telerobot with six joints, the experimental results demonstrate that thanks to the kinematic redundancy obstacle adaptation is realized and an operator can concentrate on primary tasks without any care for obstacle contact.

Strichartz estimates and the nonlinear Schrödinger equation on manifolds with boundary

We establish Strichartz estimates for the Schrödinger equation on Riemannian manifolds (Ω, g) with boundary, for both the compact case and the case that Ω is the exterior of a smooth, non-trapping obstacle in Euclidean space. The estimates for exterior domains are scale invariant; the range of Lebesgue exponents (p, q) for which we obtain these estimates is smaller than the range known for Euclidean space, but includes the key $${L^{4}_{t}L^{\infty}_x}$$ estimate, which we use to give a simple proof of well-posedness results for the energy critical Schrödinger equation in 3 dimensions. Our estimates on compact manifolds involve a loss of derivatives with respect to the scale invariant index. We use these to establish well-posedness for finite energy data of certain semilinear Schrödinger equations on general compact manifolds with boundary.

A Continuous Local Motion Planning Framework for Unmanned Vehicles in Complex Environments

As the complexity of an unmanned vehicle's operational environment increases so does the need to consider the obstacle space continually, and this is aided by splitting the motion planning functionality into distinct global and local layers. This paper presents a new continuous local motion planning framework, where the output and control space elements of the traditional receding horizon control problem are separated into distinct layers. This separation reduces the complexity of the local motion trajectory optimisation, enabling faster design and increased horizon length. The focus of this paper is on the output space component of this framework. Bezier polynomial functions are used to describe local motion trajectories which are constrained to vehicle performance limits and optimised to track a global trajectory. Development and testing is in simulation, targeted at a nonlinear model of a quadrotor unmanned air vehicle. The defined framework is used to provide situation-aware tracking of a global trajectory in the presence of static and dynamic obstacles, as well as realistic turbulence and gusts. Also demonstrated is the immediate-term decentralised deconfliction of multiple unmanned vehicles, and multiple formations of unmanned vehicles.

Stress-gradient plasticity

A new model, stress-gradient plasticity, is presented that provides unique mechanistic insight into size-dependent phenomena in plasticity. This dislocation-based model predicts strengthening of materials when a gradient in stress acts over dislocation source-obstacle configurations. The model has a physical length scale, the spacing of dislocation obstacles, and is validated by several levels of discrete-dislocation simulations. When incorporated into a continuum viscoplastic model, predictions for bending and torsion in polycrystalline metals show excellent agreement with experiments in the initial strengthening and subsequent hardening as a function of both sample-size dependence and grain size, when the operative obstacle spacing is proportional to the grain size.

Decision-making by nematodes in complex microfluidic mazes

Nematodes are microscopic, soil-dwelling worms that navigate through soil particles in search of food or a suitable host. Most nematode species employ a myriad of physical and chemical cues that define their navigation strategies. Here, we demonstrate a microfluidic method to observe and characterize the physical aspects of nematode navigation at real-time. The microfluidic devices comprise a series of interconnected T-maze or cylindrical structures of varying geometry. At each physical intersection, nematodes are given the choice to migrate left or right. We found that this decision-making of nematodes is influenced by the angle of intersection of T-maze structures. We further showed that nematodes can be passively directed to move in a linear direction by carefully adjusting the position and spacing of cylindrical obstacles in its path. The experiments were conducted on two nematodes (non-parasitic C. elegans and pigparasitic Oesophagostomum dentatum) and in the absence of any chemical or electrical stimulants.

Closed-loop Locomotion Analyzer for Investigating Context-dependent Collision Avoidance Systems in Insects

Insects are capable of extremely rapid collision avoidance behaviors with a minimum of processing overhead. These features make them interacting for robotics. To implement the strategies of insect in mobile robots or cars, a through evaluation of these systems is necessary. We developed a closed-loop experimental system for analyzing insect collision avoidance behavior in virtual environments. In the current implementation, a tethered female cricket walks on a floating sphere and the rotations of the sphere are translated into movements of a “virtual cricket” in a computer-generated virtual space. Visual information including obstacle and background patterns in the virtual space are then fed back to the tethered cricket as visual stimuli projected onto a screen in front of the cricket. To induce reliably reproducible straight-line walking, we applied the male calling song that induces positive phonotaxis in female crickets. We demonstrated that the tethered female cricket displayed collision avoidance behavior in response to visual stimuli during positive phonotaxis. By employing this system, we investigated a key stimulus that triggered collision avoidance behavior in crickets in different behavioral contexts: a cricket approaching a static object and an object moving towards a quiescent cricket. The results indicate that crickets used a certain threshold of image size (visual angle) of the projected object as a key stimulus. Furthermore, we found that the threshold depended on the behavioral context: quiescent crickets started avoidance farther from the approaching object compared to crickets walking towards a static object. We conclude that behavioral context is an important factor in decision making. With our closed-loop system for behavioral analysis, we can systematically extract the conditions under which optimal behavioral performance is obtained. This will be an important step in the design of sensory processors for robots.

2P1-F07 車輪型移動ロボットによるハーネスを用いた人誘導走行法(福祉ロボティクス・メカトロニクス(1))

We have been developed an autonomous running method which run a wheeled mobile robot to a goal while avoiding obstacles in uncertain space. This paper describes an autonomous running method to guide the blind person to goal by a wheeled robot with a harness. A speed of robot can be control by according to the corresponding angle and expansion values of the harness holding by a person.

휴머노이드 로봇을 위한 비전기반 장애물 회피 시스템 개발

This paper addresses the vision based autonomous walking control system. To handle the obstacles which exist beyond the field of view(FOV), we used the 3d panoramic depth image. Moreover, to decide the avoidance direction and walking motion of a humanoid robot for the obstacle avoidance by itself, we proposed the vision based path planning using 3d panoramic depth image. In the vision based path planning, the path and walking motion are decided under environment condition such as the size of obstacle and available avoidance space. The vision based path planning is applied to a humanoid robot, URIA. The results from these evaluations show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a practical humanoid robot.

The Origins of Strategic Communication: Precedents and Parallels in Ancient States

When, where, and why did communication strategy originate? Global communication strategy is a present-day preoccupation, but ancient states were the first to manage messages over large distances and time periods. They did this to entrench a permanent, convincing identity that embodied political power. To achieve their goal other forms of power were exploited and expressed as organized communication including religion, armed force, and administration. Early states created a distinct process to legitimize leadership and counter time and space obstacles like slow communication media, regional diversity, and the challenge to collective memory posed by limited access to written information and instruction. This article examines historical research and suggests that advanced strategic communication knowledge existed in premodern societies.

Origin of Plasticity Length-Scale Effects in Fracture

Fracture in metals is controlled by material behavior around the crack tip where size-dependent plasticity, now widely demonstrated at the micron scale, should play a key role. Here, a physical origin of the controlling length scales in fracture is identified using discrete-dislocation plasticity simulations. Results clearly demonstrate that the spacing between obstacles to dislocation motion controls fracture toughness. The simulations support a continuum strain-gradient plasticity model and provide a physical interpretation for that model's phenomenological length scale. Analysis of a dislocation pileup under a stress gradient predicts the yield stress to increase with increasing obstacle spacing, physically rationalizing the simulations.

Compact internal representation of dynamic situations: neural network implementing the causality principle

Animals for survival in complex, time-evolving environments can estimate in a "single parallel run" the fitness of different alternatives. Understanding of how the brain makes an effective compact internal representation (CIR) of such dynamic situations is a challenging problem. We propose an artificial neural network capable of creating CIRs of dynamic situations describing the behavior of a mobile agent in an environment with moving obstacles. The network exploits in a mental world model the principle of causality, which enables reduction of the time-dependent structure of real situations to compact static patterns. It is achieved through two concurrent processes. First, a wavefront representing the agent's virtual present interacts with mobile and immobile obstacles forming static effective obstacles in the network space. The dynamics of the corresponding neurons in the virtual past is frozen. Then the diffusion-like process relaxes the remaining neurons to a stable steady state, i.e., a CIR is given by a single point in the multidimensional phase space. Such CIRs can be unfolded into real space for execution of motor actions, which allows a flexible task-dependent path planning in realistic time-evolving environments. Besides, the proposed network can also work as a part of "autonomous thinking", i.e., some mental situations can be supplied for evaluation without direct motor execution. Finally we hypothesize the existence of a specific neuronal population responsible for detection of possible time-space coincidences of the animal and moving obstacles.

Nanoscale simulations of directional locking

When particles suspended in a fluid are driven through a regular lattice of cylindrical obstacles, their average motion is usually not in the direction of the force, and in the high Péclet number limit, particles tend to lock into periodic trajectories along certain lattice directions. By means of molecular dynamics simulations we show that this effect persists for nanometer-sized particles and in the presence of molecular diffusion, provided the Péclet number is not very small. The main effect of diffusion is to smooth the sharp transitions between locking directions found in the convective limit and to suppress the higher-order locking directions. We show that trajectory locking is independent of the driving mechanism and qualitatively insensitive to the particle and obstacle size and spacing. The absolute roughness of the solid surfaces is found to be the relevant quantity in locking. We observe trajectory locking in all cases, and in particular in semidilute suspensions of particles of different sizes. The degree of locking varies with particle size, and therefore these flows can have application as a nanoparticle separation technique.

Strength Effects in Micropillars of a Dispersion Strengthened Superalloy

AbstractThe present paper investigates the uniaxial compression behavior of highly alloyed, focused ion beam (FIB) manufactured micropillars, ranging from 200 up to 4000 nm in diameter. The material used was the Ni‐based oxide‐dispersion strengthened (ODS) alloy Inconel MA6000. Stress–strain curves show a change in slip behavior comparable to those observed in pure fcc metals. Contrary to pure Ni pillar experiments, high critical resolved shear stress (CRSS) values were found independent of pillar diameter. This suggests that the deformation behavior is primarily controlled by the internal obstacle spacing, overwhelming any pillar‐size‐dependent mechanisms such as dislocation source action or starvation.

Effect of source and obstacle strengths on yield stress: A discrete dislocation study

The combined effect of dislocation source strength τ s , dislocation obstacle strength τ obs , and obstacle spacing L obs on the yield stress of single crystal metals is investigated analytically and numerically. A continuum theory of dislocation pileups emanating from a finite-strength source and impinging on asymmetric obstacles gives a closed-form expression for the yield stress. A 2d discrete dislocation model for a single-source/obstacle problem agrees well with the analytic model over a wide range of material parameters. Discrete dislocation simulations for a full tensile bar with statistically distributed sources and obstacles show that the distribution of obstacles plays a significant role in controlling the yield stress. Over a wide range of parameters, the simulations agree well with the analytic model using an effective obstacle spacing L obs * chosen to capture the strength-controlling statistically weaker pileup configurations. The analytic model can thus be used to guide the choice of source and obstacle parameters to obtain a desired yield stress. The model also shows how different combinations of internal source and obstacle parameters can generate the same macroscopic yield stress, and points to several internal length scales that could relate to size-dependent plasticity phenomena.

Characterization of subglacial landscapes by a two-parameter roughness index

AbstractPrevious studies using Fourier transformation (FT) methods to analyze subglacial roughness have shown promise for distinguishing between different types of subglacial landscape from raw subglacial elevation data. We derive a two-parameter FT roughness index {ξ, η}, where • is based on the FT of elevation (as previously considered in isolation), and η is based on both the FT of elevation and the FT of bed-slope profile. In this way, we take account of both vertical and horizontal irregularities in subglacial surfaces. We demonstrate the statistical veracity of using {ξ, η} to consider roughness in terms of obstacle amplitudes and spacing, and consider the use of {ξ, η} in studies of ice dynamics and subglacial geomorphological interpretation. We show that {ξ, η} can be linked to basal sliding rates on the metre scale, and can be used to differentiate further than single-parameter roughness indices between different classes of subglacial landscape, in particular between erosional and depositional settings.

Good-visibility maps visualization

Given a set V of viewpoints and a set S of obstacles in an environmental space, the good-visibility depth of a point q in relation to V and S is a measure of how deep or central q is with respect to the points in V that see q while minding the obstacles of S. The good-visibility map determined by V and S is the subdivision of the environmental space in good-visibility regions where all points have the same fixed good-visibility depth. In this paper we present algorithms for computing and efficiently visualizing, using graphics hardware capabilities, good-visibility maps in the plane as well as on triangulated terrains, where the obstacles are the terrain faces. Finally, we present experimental results obtained with the implementation of our algorithms.

시각 장애인 보행안내를 위한 장애물 분포의 3차원 검출 및 맵핑

In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

A conical wave approach to calculating Bessel–Gauss beam reconstruction after complex obstacles

We present an efficient method to accurately calculate the reconstruction properties of a Bessel–Gauss beam after an arbitrary obstruction. Our method makes use of the well-known conical wave features of Bessel–Gauss beams, by considering the projection of the obstacle in space as a result of the travelling conical waves that produce the Bessel–Gauss beams. This approach, of projecting the obstacle boundaries rather than propagating the field itself, results in fast and accurate predictions of the field after any obstacle. We successfully predict the reconstruction properties of a Bessel–Gauss beam after three complex obstacles by calculating the boundaries of the various projected regions. This method has no restrictions regarding the geometry of the obstacle or its placement in the Bessel–Gauss field.