Showing papers on "Obstacle published in 2012"

A dynamical system approach to realtime obstacle avoidance

Abstract: This paper presents a novel approach to real-time obstacle avoidance based on Dynamical Systems (DS) that ensures impenetrability of multiple convex shaped objects. The proposed method can be applied to perform obstacle avoidance in Cartesian and Joint spaces and using both autonomous and non-autonomous DS-based controllers. Obstacle avoidance proceeds by modulating the original dynamics of the controller. The modulation is parameterizable and allows to determine a safety margin and to increase the robot's reactiveness in the face of uncertainty in the localization of the obstacle. The method is validated in simulation on different types of DS including locally and globally asymptotically stable DS, autonomous and non-autonomous DS, limit cycles, and unstable DS. Further, we verify it in several robot experiments on the 7 degrees of freedom Barrett WAM arm.

Vehicle periphery monitoring device

Abstract: A vehicle periphery monitoring device with which, when recognizing an obstacle, it is possible to easily determine the positional relationship between the obstacle and a landscape included in a video image of the vehicle periphery, generates as a notable video image a narrow viewing area that is a part of the video image. When an obstacle area, which is the area of the recognized obstacle in the video image, exists outside the narrow viewing area, and is included in an image area that is partially overlapped with said narrow viewing area and is a part of the video image, the vehicle periphery monitoring device generates said image area as a notable obstacle image. A display image for monitoring the periphery, which is comprised of the notable video image and the notable obstacle image, is generated.

Remote control for a parking assistance system and a parking assistance system which can be controlled by remote control

Abstract: One aspect of the invention relates to a remote control for a parking assistance system which can be controlled by remote control and has the purpose of automatically parking a passenger car in a parking space. The system is preferably a parking assistance system for frontal parking in a head parking space (for example an individual garage). The parking assistance system comprises a surroundings sensor system with supplies sensor information. Furthermore, an obstacle detection device is provided for detecting the presence of an obstacle on the basis of the sensor information from the surroundings sensor system. In addition, a bidirectional communication device is present. The latter transmits obstacle detection information, determined by means of the obstacle detection device, relating to the presence of an obstacle to the remote control. The remote control comprises a bidirectional communication device for wireless communication with the passenger car. In addition, one or more parking function operator controls are provided for controlling the parking in the space and/or exiting from the space. The bidirectional communication device is configured to receive obstacle detection information which is determined by means of the obstacle detection device. In addition, the remote control comprises signalling means for signalling the presence of an obstacle to the operator of the remote control as a function of the obstacle detection information.

Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning

Abstract: This paper proposes a new approach for solving the problem of obstacle avoidance during manipulation tasks performed by redundant manipulators. The developed solution is based on a double neural network that uses Q-learning reinforcement technique. Q-learning has been applied in robotics for attaining obstacle free navigation or computing path planning problems. Most studies solve inverse kinematics and obstacle avoidance problems using variations of the classical Jacobian matrix approach, or by minimizing redundancy resolution of manipulators operating in known environments. Researchers who tried to use neural networks for solving inverse kinematics often dealt with only one obstacle present in the working field. This paper focuses on calculating inverse kinematics and obstacle avoidance for complex unknown environments, with multiple obstacles in the working field. Q-learning is used together with neural networks in order to plan and execute arm movements at each time instant. The algorithm developed for general redundant kinematic link chains has been tested on the particular case of PowerCube manipulator. Before implementing the solution on the real robot, the simulation was integrated in an immersive virtual environment for better movement analysis and safer testing. The study results show that the proposed approach has a good average speed and a satisfying target reaching success rate.

Wearable obstacle detection system fully integrated to textile structures for visually impaired people

Abstract: In this study, an innovative wearable obstacle detection system fully integrated to textile structures, which enables detection of obstacles for visually impaired people, has been developed. In order to guide visually impaired people safely and quickly among obstacles, an innovative approach based on integration of electronics onto textiles has been studied. Adaptation of sensor and actuator methodology to textile structures has been realized. Finally, smart clothing prototype including ultrasonic sensors, vibration motors, power supplies and a microcontroller has been developed. The working principle of the system is based on two main functions: sensing the surrounding environment as well as detection of obstacles via sonar sensors and guiding the user by actuators by using a novel control algorithm based on a neuro-fuzzy controller implemented to a processing unit. This system is able to identify obstacle's position within the detection range. It is capable of detecting obstacle's position accurately. It is easily worn as a garment that is flexible, lightweight and comfortable for human body as well as washable. The proposed smart clothing system could become united part of visually impaired people's lifestyle, and it could help them overcome navigation concerns seamlessly, without imposing upon them any physical or cognitive load.

Guaranteed infinite horizon avoidance of unpredictable, dynamically constrained obstacles

Abstract: This paper presents a new approach to guaranteeing collision avoidance with respect to moving obstacles that have constrained dynamics but move unpredictably. Velocity Obstacles have been used previously to plan trajectories that avoid collisions with obstacles under the assumption that the trajectories of the objects are either known or can be accurately predicted ahead of time. However, for real systems this predicted trajectory will typically only be accurate over short time-horizons. To achieve safety over longer time periods, this paper instead considers the set of all reachable points by an obstacle assuming that the dynamics fit the unicycle model, which has known constant forward speed and a maximum turn rate (sometimes called the Dubins car model). This paper extends the Velocity Obstacle formulation by using reachability sets in place of a single "known" trajectory to find matching constraints in velocity space, called Velocity Obstacle Sets. The Velocity Obstacle Set for each obstacle is equivalent to the union of all velocity obstacles corresponding to any dynamically feasible future trajectory, given the obstacle's current state. This region remains bounded as the time horizon is increased to infinity, and by choosing control inputs that lie outside of these Velocity Obstacle Sets, it is guaranteed that the host agent can always actively avoid collisions with the obstacles, even without knowing their exact future trajectories. Furthermore it is proven that, subject to certain initial conditions, an iterative planner under these constraints guarantees safety for all time. Such an iterative planner is implemented and demonstrated in simulation.

Controls on local scour and deposition induced by obstacles in fluvial environments

Abstract: Obstacles in fluvial environments cause flow separation and the emergence of three-dimensional flow fields that can lead to scour and deposition, even when no general sediment transport at the bed occurs. Resulting forms are commonly denoted as ‘fluvial obstacle marks’. The morphology and dynamics of these forms is depended on obstacle-, flow- and sediment characteristics. As no generally approved approach for analysis of these forms exists yet, a process-based method is developed that relates certain dependent morphometric variables to an adapted obstacle Reynolds number. The novel approach was applied by conducting experiments in a laboratory flume and validated against other laboratory and field data. The results of this work have shown a significant relationship between the morphometry of fluvial obstacle marks and obstacle Reynolds number, especially when morphometric variables were combined. Further validation, calibration and extension and of this approach will help to adequately asses the influence of obstacles in the fluvial environment on micro- and meso-scale processes of sediment transport.

Flow and clogging in a silo with an obstacle above the orifice.

Abstract: In a recent paper [Zuriguel et al., Phys. Rev. Lett. 107, 278001 (2011)] it has been shown that the presence of an obstacle above the outlet can significatively reduce the clogging probability of granular matter pouring from a silo. The amount of this reduction strongly depends on the obstacle position. In this work, we present new measurements to analyze different outlet sizes, extending foregoing results and revealing that the effect of the obstacle is enhanced as the outlet size is increased. In addition, the effect of the obstacle position on the flow rate properties and in the geometrical features of arches is studied. These results reinforce previous evidence of the pressure reduction induced by the obstacle. In addition, it is shown how the mean avalanche size and the average flow rate are not necessarily linked. On the other hand, a close relationship is suggested between the mean avalanche size and the flow rate fluctuations.

Generating obstacle conditions for requirements completeness

Abstract: Missing requirements are known to be among the major causes of software failure. They often result from a natural inclination to conceive over-ideal systems where the software-to-be and its environment always behave as expected. Obstacle analysis is a goal-anchored form of risk analysis whereby exceptional conditions that may obstruct system goals are identified, assessed and resolved to produce complete requirements. Various techniques have been proposed for identifying obstacle conditions systematically. Among these, the formal ones have limited applicability or are costly to automate. This paper describes a tool-supported technique for generating a set of obstacle conditions guaranteed to be complete and consistent with respect to the known domain properties. The approach relies on a novel combination of model checking and learning technologies. Obstacles are iteratively learned from counterexample and witness traces produced by model checking against a goal and converted into positive and negative examples, respectively. A comparative evaluation is provided with respect to published results on the manual derivation of obstacles in a real safety-critical system for which failures have been reported.

Experimental Investigation of Electromagnetic Obstacle Detection for Visually Impaired Users: A Comparison With Ultrasonic Sensing

Abstract: The use of electromagnetic (EM) fields for obstacle detection to aid mobility of visually impaired people is presented in this paper. The method proposed is based on the launch of EM pulses and on the measurement of the reflected signal which explores a region in front of the user of about 3 m. A laboratory system is set up, its performances (detecting the presence and the distance of obstacles) are investigated, and the measurements are compared with the data measured by an ultrasonic obstacle detection system. Results show that, with the EM system, all the obstacles tested (up to a minimum size of 3 cm × 3 cm, at a distance of 3 m) are correctly detected, as well as some specific targets (a chain, a pole, etc.) that are not visible by the ultrasonic system. The EM system has been tested in indoor and outdoor cluttered scenarios at the presence of real obstacles (single and multiple), and in all cases, it detects their presence with a signal-to-noise ratio ranging from 10 to 23 dB. Despite the use of a laboratory system, still not specifically designed for daily use, this paper demonstrates the possibility of adopting EM held pulses for obstacle detection, highlighting advantages with respect to ultrasonic systems and addressing future research activity to design an improved ad hoc EM system.

Adaptive artificial potential field approach for obstacle avoidance of unmanned aircrafts

Abstract: In this paper, a novel approach for obstacle avoidance of unmanned aircrafts is introduced. To avoid collision, a potential field whose vectors are rotating around the obstacle is proposed. Most approaches using potential field in the literature repulse unmanned vehicles to get them far from obstacles. In a case that a vehicle approaches an obstacle exactly in the opposite direction of the repulsive vectors, the vehicle may locate in a local minima position and its speed converges to zero. The proposed technique in this paper considers constrains on motion control of unmanned aircrafts. The introduced rotational potential field is adaptive with the attitude of an approaching unmanned aircraft and its relative position to the obstacle to avoid making it slow down and stick in local minima positions. The simulation results confirm the feasibility of the proposed approach.

Effective navigation for visually impaired by wearable obstacle avoidance system

Abstract: This paper presents a wearable obstacle avoidance system for blind people to navigate safely using cane and eyeglass methods. In cane method, an ultrasonic sensor is placed in cane which detects the obstacle in the ground level. In eyeglass method, an ultrasonic sensor is used which detects obstacle above the head up to certain angle. The information obtained is informed to users using audio messages and also by sense of feel as vibration in case of born both deaf and blind. These algorithms are implemented using MP Lab and Proteus tools.

Sliding door obstacle detection

Abstract: Obstacle detection for a sliding door of a vehicle including a sensor apparatus located on or near a hinge of the sliding door and arranged to detect an obstacle in a path of the hinge of the sliding door. A controller connected to the sensor apparatus is configured to receive an obstruction signal from the sensor apparatus indicating detection of an obstacle in the path of the hinge of the sliding door.

A practical obstacle detection system for autonomous orchard vehicles

Abstract: Safe robot navigation in tree fruit orchards requires that the vehicle be capable of robustly navigating between rows of trees and turning from one aisle to another; that the vehicle be dynamically stable, especially when carrying workers; and that the vehicle be able to detect obstacles on its way and adjust its speed accordingly. In this paper we address the latter, in particular the problem of detecting people and apple bins in the aisles between rows. One of our requirements is that the obstacle avoidance subsystem shouldn't add to the robot's hardware cost, so as to keep the acquisition cost to growers as low as possible. Therefore, we confine ourselves to solutions that use only the sensor suite already installed on the robot for navigation-in our case, a laser scanner, low-cost inertial measurement unit, and steering and wheel encoders. Our methodology is based on the classification and clustering of registered 3D points as obstacles. In the current implementation, obstacle avoidance takes in 3D point clouds collected in apple orchards and generates an off-line assessment of obstacle position. Tests conducted at our experimental orchard-like environment in Pittsburgh and an actual apple orchard in Washington state indicate that the method is able to detect people and bins located along the vehicle path. Stretch tests indicate that it is also capable of dealing with objects as small as 15 cm tall as long as they aren't covered by grass, and to detect people crossing the aisles at walking speed.

Analytical study on the self-healing property of Bessel beam

Abstract: With the help of Babinet principle, an analytical expression for the self-healing of Bessel beam is derived by using the Gaussian absorption function to describe the obstacle. Based on the analytical expression, the self-healing properties of Bessel beam are studied. It shows that Bessel beam has the ability to reconstruct its beam shape disturbed by an obstacle. However, during the self-healing process, not only the intensity of the beam behind the obstacle but also the other part will be affected by the obstruction. Meanwhile, the highlight spot, which intensity is larger than that without the obstacle will appear, and the size and strength of the highlight spot is determined by the size of the obstacle. From the change of Poynting vector and Babinet principle, the physical interpretations for the self-healing ability, the effects of the obstruction on the other part and the appearance of highlight spot are given.

An intelligent depth-based obstacle detection system for visually-impaired aid applications

Abstract: In this paper, we present a robust depth-based obstacle detection system in computer vision. The system aims to assist the visually-impaired in detecting obstacles with distance information for safety. With analysis of the depth map, segmentation and noise elimination are adopted to distinguish different objects according to the related depth information. Obstacle extraction mechanism is proposed to capture obstacles by various object proprieties revealing in the depth map. The proposed system can also be applied to emerging vision-based mobile applications, such as robots, intelligent vehicle navigation, and dynamic surveillance systems. Experimental results demonstrate the proposed system achieves high accuracy. In the indoor environment, the average detection rate is above 96.1%. Even in the outdoor environment or in complete darkness, 93.7% detection rate is achieved on average.

UAV obstacle avoidance using image processing techniques

Abstract: Novel algorithms were developed for use on a low-price, consumer four-rotor helicopter with limited on-board computational capacity. Simplified occupancy grid maps, basic wall-following and obstacle avoidance were constructed from laser rangefinder data using image processing primitives in OpenCV. These algorithms generated obstacle free paths along walls in preliminary testing. The resulting system will allow untrained and unskilled users to teleoperate a low-cost flight platform, assembled from commercially available parts for remote exploration in quasi-static indoor environments.

A probabilistic framework for goal-oriented risk analysis

Abstract: Requirements completeness is among the most critical and difficult software engineering challenges. Missing requirements often result from poor risk analysis at requirements engineering time. Obstacle analysis is a goal-oriented form of risk analysis aimed at anticipating exceptional conditions in which the software should behave adequately. In the identify-assess-control cycles of such analysis, the assessment step is not well supported by current techniques. This step is concerned with evaluating how likely the obstacles to goals are and how likely and severe their consequences are. Those key factors drive the selection of most appropriate countermeasures to be integrated in the system goal model for increased completeness. Moreover, obstacles to probabilistic goals are currently not supported; such goals prescribe that some corresponding target property should be satisfied in at least X% of the cases. The paper presents a probabilistic framework for goal specification and obstacle assessment. The specification language for goals and obstacles is extended with a probabilistic layer where probabilities have a precise semantics grounded on system-specific phenomena. The probability of a root obstacle to a goal is thereby computed by up-propagation of probabilities of finer-grained obstacles through the obstacle refinement tree. The probability and severity of obstacle consequences is in turn computed by up-propagation from the obstructed leaf goals through the goal refinement graph. The paper shows how the computed information can be used to prioritize obstacles for countermeasure selection towards a more complete and robust goal model. The framework is evaluated on a non-trivial carpooling support system.

Optimizing and Post Processing of a Smart Beamformer for Obstacle Retrieval

Abstract: Beamforming is one of the most interesting techniques used to know distance systems in order to detect punctual, widespread obstacles. If correctly associated to DOA (Difference of Arrival), it can allow the description of obstacle shape. Distance ranging, for mobile and fixed systems, namely cars, vehicles, vessels and airplanes, that is a key issue for demands of nowadays. Distance between cars and from obstacles can be established and measured using laser and ultrasound. Cloudy and foggy conditions are very important requirements for testing distance ranging facilities. If based on acoustic waves, they can be easily integrated by sophisticated on-board software in order to perform new features. This research presents interesting aspects of defining new requirements for an acoustic scanning capable of reconstructing fixed obstacle features by targeting them using a special array of sensors. The term “acoustic scanning” is intended here as an aspect of sound ranging and reproduction regarding spatial locations of the obstacle, that is spatial shaping. The paper illustrates first an experimental system from which it is possible to derive parameters for setting spatial shaping of scenarios and after a clear identification of DOAs.

Inverse obstacle scattering with limited-aperture data

Abstract: Inverse obstacle scattering aims to extract information about distant and unknown targets using wave propagation. This study concentrates on a two-dimensional setting using time-harmonic acoustic plane waves as incident fields and taking the obstacles to be sound-hard with smooth or polygonal boundary. Measurement data is simulated by sending one incident wave towards the area of interest and computing the far field pattern (1) on the whole circle of observation directions, (2) only in directions close to backscattering, and (3) only in directions close to forward-scattering. A variant of the enclosure method is introduced, based on applying the far field operator to an explicitly constructed density, yielding information about the convex hull of the obstacle. The numerical evidence presented suggests that the convex hull of obstacles can be approximately recovered from noisy limited-aperture far field data.

Particle Grid Tracking System Stereovision Based Obstacle Perception in Driving Environments

Abstract: This paper presents an occupancy grid tracking system based on particles, and the use of this system for dynamic obstacle detection in driving environments. The particles will have a dual nature they will denote hypotheses, as in the particle filtering algorithms, but they will also be the building blocks of our modeled world. The particles have position and speed, and they can migrate in the grid from cell to cell depending on their motion model and motion parameters, but they will also be created and destroyed using a weighting-resampling mechanism specific to particle filter algorithms. An obstacle grid derived from processing a stereovision-generated elevation map is used as measurement information, and the measurement model takes into account the uncertainties of the stereo reconstruction. The dynamic occupancy grid is used for improving the quality of the stereovision-based reconstruction as oriented cuboids. The resulted system is a flexible, real-time tracking solution for dynamic unstructured driving environments, and a useful tool for extracting intermediate dynamic information that can considerably improve object detection and tracking.

Obstacle detection apparatus and obstacle detection program

Abstract: An obstacle detection apparatus includes a transmission antenna transmitting radio waves, a reception antenna receiving radio waves transmitted to and reflected by an obstacle, an obstacle detection unit configured to detect the obstacle based on the received radio waves, a false detection determination unit configured to determine presence or absence of a false detection characteristic, which is set in advance, with regard to the detected obstacle, a camera capturing an image, and an obstacle existence determination unit configured to determine, based on the image captured by the camera, presence or absence of the obstacle on which it is determined that the false detection characteristic is present.

Higher integrability in parabolic obstacle problems

Abstract: Abstract. In this paper we establish the self-improving property of integrability for parabolic variational inequalities satisfying an obstacle constraint and involving possibly degenerate respectively singular operators in divergence form. In particular, our results apply to the model case of the variational inequality associated to the parabolic p-Laplacean operator. Thereby we do not impose any monotonicity assumption in time on the obstacle function.

A new fuzzy intelligent obstacle avoidance control strategy for wheeled mobile robot

Abstract: Obstacle avoidance is the basic requirement for any autonomous mobile robot. Fuzzy intelligent obstacle avoidance strategy is proposed in this paper for the wheeled mobile robot tracking a target in the environment with obstacles, which is composed of two fuzzy logic controllers and an intelligent coordinator. Run-to-goal fuzzy controller makes the robot approach the target when there are no obstacles in the environment; Fuzzy obstacle controller will generate obstacle avoidance commands according to target orientation information and obstacle information when the robot detecting obstacles via its onboard sensors. Intelligent coordinator is designed to coordinate the two actions mentioned above to generate robot's ultimate control command. Ultimately, the robot tracks the target and realizes obstacle avoidance meanwhile. Simulations and experiments on robot platform validate the effectiveness proposed by the paper.

Performance and three-dimensional kinematics of bipedal lizards during obstacle negotiation

Abstract: Bipedal running is common among lizard species, but although the kinematics and performance of this gait have been well characterized, the advantages in biologically relevant situations are still unclear. Obstacle negotiation is a task that is ecologically relevant to many animals while moving at high speeds, such as during bipedal running, yet little is known about how obstacles impact locomotion and performance. We examined the effects of obstacle negotiation on the kinematics and performance of lizards during bipedal locomotion. We quantified three-dimensional kinematics from high-speed video (500 Hz) of six-lined racerunners ( Aspidoscelis sexlineata ) running on a 3 m racetrack both with and without an obstacle spanning the width of the track. The lizards did not alter their kinematics prior to contacting the obstacle. Although contact with the obstacle caused changes to the hindlimb kinematics, mean forward speed did not differ between treatments. The deviation of the vertical position of the body center of mass did not differ between treatments, suggesting that in the absence of a cost to overall performance, lizards forgo maintaining normal kinematics while negotiating obstacles in favor of a steady body center of mass height to avoid destabilizing locomotion.

Reactive Path Planning for Micro Air Vehicles Using Bearing-only Measurements

Abstract: Autonomous path planning of Micro Air Vehicles (MAVs) in an urban environment is a challenging task because urban environments are dynamic and have variety of obstacles, and the locations of these obstacles may not be available a priori. In this paper we develop a reactive guidance strategy for collision avoidance using bearing-only measurements. The guidance strategy can be used to avoid collision from circular obstacles and to follow straight and curved walls at safe distance. The guidance law moves a obstacle in the sensor field-of-view to a desired constant bearing angle, which causes the MAV to maintain a constant distance from the obstacle. We use sliding mode control theory to derive the guidance law, which is fast, computationally inexpensive, and guarantees collision avoidance.

Overcoming obstacles: the effect of obstacles on locomotor performance and behaviour

Abstract: Sprinting and jumping ability are key performance measures that have been widely studied in vertebrates. The vast majority of these studies, however, use methodologies that lack an ecological context by failing to consider the complex habitats in which many animals live. Because successfully navigating obstacles within complex habitats is critical for predator escape, running, climbing, and/or jumping performance are each likely to be exposed to selection. In the present study, we quantify how behavioural strategies and locomotor performance change with increasing obstacle height. Obstacle size had a significant influence on behaviour (e.g. obstacle crossing strategy, intermittent locomotion) and performance (e.g. sprint speed, jump distance). Jump frequency and distance increased with obstacle size, suggesting that it likely evolved because it is more efficient (i.e. it reduces the time and distance required to reach a target position). Jump angle, jump velocity, and approach velocity accounted for 58% of the variation in jump distance on the large obstacle, and 33% on the small obstacle. Although these variables have been shown to significantly influence jump distance in static jumps, they do not appear to be influential in running (dynamic) jumps onto a small obstacle. Because selection operates in simple and complex habitats, future studies should consider quantifying additional measures such as jumping or climbing with respect to the evolution of locomotion performance. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ••, ••–••.

A new tentacles-based technique for avoiding obstacles during visual navigation

Abstract: In this paper, we design and validate a new tentacle-based approach, for avoiding obstacles during appearance-based navigation with a wheeled mobile robot. In the past, we have developed a framework for safe visual navigation. The robot follows a path represented as a set of key images, and during obstacle circumnavigation, the on-board camera is actuated to maintain scene visibility. In those works, the model used for obstacle avoidance was obtained using a potential vector field. Here, a more sophisticated and efficient method, that exploits the robot kinematic model, and predicts collision at look-ahead distances, is designed and integrated in that framework. Outdoor experiments comparing the two models show that the new approach presents many advantages. Higher speeds and precision can be attained, very cluttered scenarios involving large obstacles can be successfully dealt with, and the control inputs are smoother.