Showing papers on "Obstacle published in 2013"

First results in detecting and avoiding frontal obstacles from a monocular camera for micro unmanned aerial vehicles

Abstract: Obstacle avoidance is desirable for lightweight micro aerial vehicles and is a challenging problem since the payload constraints only permit monocular cameras and obstacles cannot be directly observed. Depth can however be inferred based on various cues in the image. Prior work has examined optical flow, and perspective cues, however these methods cannot handle frontal obstacles well. In this paper we examine the problem of detecting obstacles right in front of the vehicle. We developed a method to detect relative size changes of image patches that is able to detect size changes in the absence of optical flow. The method uses SURF feature matches in combination with template matching to compare relative obstacle sizes with different image spacing. We present results from our algorithm in autonomous flight tests on a small quadrotor. We are able to detect obstacles with a frame-to-frame enlargement of 120% with a high confidence and confirmed our algorithm in 20 successful flight experiments. In future work, we will improve the control algorithms to avoid more complicated obstacle configurations.

Contingency Planning Over Probabilistic Obstacle Predictions for Autonomous Road Vehicles

Abstract: This paper presents a novel optimization-based path planner that is capable of planning multiple contingency paths to directly account for uncertainties in the future trajectories of dynamic obstacles. This planner addresses the particular problem of probabilistic collision avoidance for autonomous road vehicles that are required to safely interact, in close proximity, with other vehicles with unknown intentions. The presented path planner utilizes an efficient spline-based trajectory representation and fast but accurate collision probability bounds to simultaneously optimize multiple continuous contingency paths in real time. These collision probability bounds are efficient enough for real-time evaluation, yet accurate enough to allow for practical close-proximity driving behaviors such as passing an obstacle vehicle in an adjacent lane. An obstacle trajectory clustering algorithm is also presented to enable the path planner to scale to multiple-obstacle scenarios. Simulation results show that the contingency planner allows for a more aggressive driving style than planning a single path without compromising the overall safety of the robot.

Data selection by an autonomous vehicle for trajectory modification

Abstract: An autonomous vehicle may determine to seek assistance navigating using a first trajectory. The autonomous vehicle may be configured to receive and store data about a plurality of obstacles. A particular obstacle in the plurality of obstacles may partially or wholly obstruct the first trajectory. The autonomous vehicle may select a portion of the stored data that includes data representing the particular obstacle. The selected portion of the stored data may be provided to an assistance center. A second trajectory may be received from the assistance center, where the second trajectory is not obstructed by the particular obstacle.

Visual navigation of a mobile robot with laser-based collision avoidance

Abstract: In this paper, we propose and validate a framework for visual navigation with collision avoidance for a wheeled mobile robot. Visual navigation consists of following a path, represented as an ordered set of key images, which have been acquired by an on-board camera in a teaching phase. While following such a path, the robot is able to avoid obstacles which were not present during teaching, and which are sensed by an on-board range scanner. Our control scheme guarantees that obstacle avoidance and navigation are achieved simultaneously. In fact, in the presence of obstacles, the camera pan angle is actuated to maintain scene visibility while the robot circumnavigates the obstacle. The risk of collision and the eventual avoiding behaviour are determined using a tentacle-based approach. The framework can also deal with unavoidable obstacles, which make the robot decelerate and eventually stop. Simulated and real experiments show that with our method, the vehicle can navigate along a visual path while avoiding collisions.

Guiding locomotion in complex, dynamic environments

Abstract: Locomotion in complex dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects -- that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach.

Supporting blind navigation using depth sensing and sonification

Abstract: We present a system designed to help blind people navigate around obstacles. Our system perceives the environment in front of the user using a depth camera (a Microsoft Kinect). The system identifies nearby structures from the depth map and uses sonification to convey obstacle information to the user. The system has undergone a formative evaluation involving eight blind-folded participants and one blind participant. We found that our system can be learned within minutes and that participants can successfully navigate through an obstacle course with few collisions.

Obstacle avoidance apparatus and obstacle avoidance method

Abstract: An obstacle detecting unit detects an obstacle for a user wearing a head mounted display from an image of the outside world. A distance calculating unit calculates the distance from a detected obstacle to the user wearing the head mounted display. An obstacle replacing unit replaces the detected obstacle with a virtual object. A virtual object synthesizing unit generates a virtual object at a position within a virtual space displayed on the head mounted display, in which the position is determined according to the distance to the obstacle.

An Optimized Field Coverage Planning Approach for Navigation of Agricultural Robots in Fields Involving Obstacle Areas

Abstract: Technological advances combined with the demand of cost efficiency and environmental considerations has led farmers to review their practices towards the adoption of new managerial approaches, including enhanced automation. The application of field robots is one of the most promising advances among automation technologies. Since the primary goal of an agricultural vehicle is the complete coverage of the cropped area within a field, an essential prerequisite is the capability of the mobile unit to cover the whole field area autonomously. In this paper, the main objective is to develop an approach for coverage planning for agricultural operations involving the presence of obstacle areas within the field area. The developed approach involves a series of stages including the generation of field-work tracks in the field polygon, the clustering of the tracks into blocks taking into account the in-field obstacle areas, the headland paths generation for the field and each obstacle area, the implementation of a genetic algorithm to optimize the sequence that the field robot vehicle will follow to visit the blocks and an algorithmic generation of the task sequences derived from the farmer practices. This approach has proven that it is possible to capture the practices of farmers and embed these practices in an algorithmic description providing a complete field area coverage plan in a form prepared for execution by the navigation system of a field robot.

Unmanned aerial vehicle obstacle avoidance controlling method

Abstract: The invention discloses an unmanned aerial vehicle obstacle avoidance controlling method. An unmanned aerial vehicle subsystem and a ground station subsystem are arranged, the unmanned aerial vehicle subsystem comprises an embedded flight controller and an airborne terminal of a wireless data chain, a satellite positioning receiver and a height sensor are arranged in the embedded flight controller, the ground subsystem comprises an embedded monitoring computer and a ground terminal of the wireless data chain, and an electronic map containing geographic information of obstacles is arranged in the embedded monitoring computer. On the electronic map in the embedded monitoring computer of the ground station subsystem, the geographic information of the obstacles in a flight area is determined, virtual obstacle polygonal cylinders are established, shape data of the virtual obstacle polygonal cylinders are downloaded in the embedded flight controller which obtains the current position of the unmanned aerial vehicle and calculates space correlation between the unmanned aerial vehicle and the obstacle polygonal cylinders, track-shifting instruction of the unmanned aerial vehicle is generated, and automatic obstacle avoidance of the unmanned aerial vehicle is realized.

Using obstacle detection to identify appropriate illuminances for lighting in residential roads

Abstract: This paper uses data regarding detection of pavement obstacles to explore two approaches to establishing an appropriate illuminance for road lighting designed to meet the needs of pedestrians. A previous obstacle detection experiment was repeated using young observers under high pressure sodium (HPS) lighting. One approach was to identify whether there is a plateau-escarpment relationship between obstacle detection ability and illuminance – better detection with increasing light level until further increases bring little improvement: This suggested an appropriate illuminance of 5.7 lux. The second approach was to identify the size of an obstacle that a pedestrian should expect to be able to detect and the associated probability of detection: An obstacle of height 25 mm located 6 m ahead may require 1.8 lux to be detected with 95% probability.

Ultrasonic and Infrared Sensors Performance in a Wireless Obstacle Detection System

Abstract: Ultrasonic (US) and infrared (IR) sensors are broadly used in mobile applications for distance measurements. In this project, an obstacle detection system is built based on these two types of sensors. The system is intended for use by the elderly and people with vision impairment. The prototype developed has been tested to detect obstacles and shows accuracies of 95% to 99% for distance measurements if the sensor circuits are calibrated properly and their output linearized. The system also demonstrates good detection for different obstacle materials (e.g., wood, plastic, mirror, plywood and concretes) and colors. The minimum size of an obstacle that the system can detect is 5 cm x 5 cm.

Multimodal obstacle detection and collision avoidance for micro aerial vehicles

Abstract: Reliably perceiving obstacles and avoiding collisions is key for the fully autonomous application of micro aerial vehicles (MAVs), Limiting factors for increasing autonomy and complexity of MAVs are limited onboard sensing and limited onboard processing power. In this paper, we propose a complete system with a multimodal sensor setup for omnidirectional obstacle perception. We developed a lightweight 3D laser scanner and visual obstacle detection using wide-angle stereo cameras. Detected obstacles are aggregated in egocentric grid maps. We implemented a fast reactive collision avoidance approach for safe operation in the vicinity of structures like buildings or vegetation.

Assessing requirements-related risks through probabilistic goals and obstacles

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 existing 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 toward a more complete and robust goal model. A detailed evaluation of our framework on a non-trivial carpooling support system is also reported.

Real-time obstacle detection and avoidance in the presence of specular surfaces using an active 3D sensor

Abstract: This paper proposes a novel approach to obstacle detection and avoidance using a 3D sensor. We depart from the approach of previous researchers who use depth images from 3D sensors projected onto UV-disparity to detect obstacles. Instead, our approach relies on projecting 3D points onto the ground plane, which is estimated during a calibration step. A 2D occupancy map is then used to determine the presence of obstacles, from which translation and rotation velocities are computed to avoid the obstacles. Two innovations are introduced to overcome the limitations of the sensor: An infinite pole approach is proposed to hypothesize infinitely tall, thin obstacles when the sensor yields invalid readings, and a control strategy is adopted to turn the robot away from scenes that yield a high percentage of invalid readings. Together, these extensions enable the system to overcome the inherent limitations of the sensor. Experiments in a variety of environments, including dynamic objects, obstacles of varying heights, and dimly-lit conditions, show the ability of the system to perform robust obstacle avoidance in real time under realistic indoor conditions.

A simple, but NP-hard, motion planning problem

Abstract: Determining the existence of a collision-free path between two points is one of the most fundamental questions in robotics. However, in situations where crossing an obstacle is costly but not impossible, it may be more appropriate to ask for the path that crosses the fewest obstacles. This may arise in both autonomous outdoor navigation (where the obstacles are rough but not completely impassable terrain) or indoor navigation (where the obstacles are doors that can be opened if necessary). This problem, the minimum constraint removal problem, is at least as hard as the underlying path existence problem. In this paper, we demonstrate that the minimum constraint removal problem is NP-hard for navigation in the plane even when the obstacles are all convex polygons, a case where the path existence problem is very easy.

A mimetic discretization of elliptic obstacle problems

Abstract: We develop a Finite Element Method (FEM) which can adopt very general meshes with polygonal elements for the numerical approximation of elliptic obstacle problems. These kinds of methods are also known as mimetic discretization schemes, which stem from the Mimetic Finite Difference (MFD) method. The first-order convergence estimate in a suitable (mesh-dependent) energy norm is established. Numerical experiments confirming the theoretical results are also presented.

Stereovision based obstacle detection system for unmanned surface vehicle

Abstract: This paper presents the stereo based obstacle detection system for unmanned surface vehicle (USV). The system is designed and developed toward the aim of real-time and robust obstacle detection and tracking at sea. Stereo vision methods and techniques have been employed to offer the capacity of detecting, locating and tracking multiple obstacles in the near field. Field test in the real scenes has been conducted, and the obstacle detection system for USV is proven to provide stable and satisfactory performance. The valid range with good accuracy of depth estimation is from 20 to 200 meters for high speed USV.

Obstacle Detection and Object Size Measurement for Autonomous Mobile Robot using Sensor

Abstract: Different types of sensors are often fused to acquire information which cannot be acquired by a single sensor. Sensor fusion is particularly applicable for mobile robots for object detection and navigation. The techniques that have been developed so far for detecting an obstacle are costly. Hence, a new technique is proposed which can detect an obstacle, judge its distance and measure the size of the obstacle using one camera and one ultrasonic sensor. The technique is cheap in terms of sensor cost and in terms of computational cost. General Terms Robotics, robot navigation.

Method and device for avoiding obstacle of unmanned aerial vehicle

Abstract: The invention provides a method and a device for avoiding an obstacle of an unmanned aerial vehicle The method comprises the following steps of: detecting and judging whether the obstacle or an emergent threat exists in the forwarding direction of the unmanned aerial vehicle in real time; if the obstacle or the emergent threat exists, establishing an obstacle region at which the obstacle or the emergent threat is located, and establishing a collision avoidance behavior region according to an obstacle side closest to the unmanned aerial vehicle in the obstacle region; if the unmanned aerial vehicle enters the collision avoidance behavior region, calculating an obstacle avoidance velocity vector according to the closest obstacle side, wherein the obstacle avoidance velocity vector comprises obstacle avoidance velocity and obstacle avoidance direction of the unmanned aerial vehicle; calculating forwarding step of the unmanned aerial vehicle according to the obstacle avoidance velocity vector obtained through calculation; if not any obstacle or emergent threat is detected, calculating a target guide velocity vector according to target position, and calculating forwarding step of the target guide velocity vector; judging whether to achieve the target, if the target is not achieved, detecting and calculating again; or ending

Autonomous vehicle obstacle avoidance method based on arc path

Abstract: The invention discloses an autonomous vehicle obstacle avoidance method based on an arc path. The autonomous vehicle obstacle avoidance method comprises the following steps of: S1, acquiring the position of a vehicle at any moment through a positioning system; S2, judging whether an obstacle exists in a specific region of a detection range or not, and if so, measuring the distance between the vehicle and the obstacle; S3, selecting a manner of advancing toward a target or walking around the obstacle by the vehicle according to an obstacle distribution condition to realize collision-free navigation towards a fixed target point in an unknown environment; and S4, adding a turning route selection mechanism in the manner of walking around the obstacle, and determining an optimal obstacle avoidance driving route according to the information of the obstacle. The autonomous vehicle obstacle avoidance method disclosed by the invention sufficiently utilizes the advantages of a BUG obstacle avoidance algorithm, and the vehicle is only required to have a detection range of 180 degrees; a physical size and a driving character of the vehicle are also considered and the problem that a four-wheeled vehicle in a non-360-degree detection range cannot use the BUG algorithm is solved; continuous and smooth by-pass movements by navigation obstacle avoidance is realized through a transition path track generated at a turning point.

Analytic extension and reconstruction of obstacles from few measurements for elliptic second order operators

Abstract: We deal with an inverse obstacle problem for general second order scalar elliptic operators with real principal part and analytic coefficients near the obstacle. We assume that the boundary of the obstacle is a non-analytic hypersurface. We show that, when we put Dirichlet boundary conditions, one measurement is enough to reconstruct the obstacle. In the Neumann case, we have results only for n = 2, 3 in general. More precisely, we show that one measurement is enough for n = 2 and we need 3 linearly independent inputs for n = 3. However, in the case for the Helmholtz equation, we only need n − 1 linearly independent inputs, for any n ≥ 2. Here n is the dimension of the space containing the obstacle. These are justified by investigating the analyticity properties of the zero set of a real analytic function. In addition, we give a reconstruction procedure for each case to recover the shape of obstacle. Although we state the results for the scattering problems, similar results are true for the associated boundary value problems.

A Priori Finite Element Error Analysis for Optimal Control of the Obstacle Problem

Abstract: An optimal control problem governed by a unilateral obstacle problem is considered. The problem is discretized using linear finite elements for the state and the obstacle and a variational discrete approach for the control. Based on strong stationarity and a quadratic growth condition we establish a priori error estimates which turn out to be quasi-optimal under additional assumptions on the data. The theoretical findings are illustrated by two numerical tests.

Mobile robot obstacle avoidance by using Fuzzy Logic technique

Abstract: This paper present an obstacle avoidance approach for e-puck module by using Fuzzy Logic controller. The input from eight (8) IR sensors and the output of the motor speed will be used to construct the Fuzzy Logic rules. Test environment, e-puck robot and Fuzzy algorithm was model and programmed by as a Webots Pro Simulation software. The Fuzzy system for e-puck robot was validated in a few environments. The result shows the e-puck module can avoid that static obstacles successfully until it reach a goal point. The robot performance in term of distance and time was recorded when the robot works in simple, average and complex obstacle environments.

Trajectory and distribution of suspended non-Brownian particles moving past a fixed spherical or cylindrical obstacle

Abstract: We investigate the motion of a suspended non-Brownian sphere past a fixed cylindrical or spherical obstacle in the limit of zero Reynolds number for arbitrary particle–obstacle aspect ratios. We consider both a suspended sphere moving in a quiescent fluid under the action of a uniform force as well as a uniform ambient velocity field driving a freely suspended particle. We determine the distribution of particles around a single obstacle and solve for the individual particle trajectories to comment on the transport of dilute suspensions past an array of fixed obstacles. First, we obtain an expression for the probability density function governing the distribution of a dilute suspension of particles around an isolated obstacle, and we show that it is isotropic. We then present an analytical expression – derived using both Eulerian and Lagrangian approaches – for the minimum particle–obstacle separation attained during the motion, as a function of the incoming impact parameter, i.e. the initial offset between the line of motion far from the obstacle and a parallel line that goes through its centre. Further, we derive the asymptotic behaviour for small initial offsets and show that the minimum separation decays exponentially. Finally we use this analytical expression to define an effective hydrodynamic surface roughness based on the net lateral displacement experienced by a suspended sphere moving past an obstacle.

Positive and negative obstacle avoidance system and method for a mobile robot

Abstract: Embodiments of the present invention provide methods and systems for ensuring that mobile robots are able to detect and avoid positive obstacles in a physical environment that are typically hard to detect because the obstacles do not exist in the same plane or planes as the mobile robot's horizontally-oriented obstacle detecting lasers. Embodiments of the present invention also help to ensure that mobile robots are able to detect and avoid driving into negative obstacles, such as gaps or holes in the floor, or a flight of stairs. Thus, the invention provides positive and negative obstacle avoidance systems for mobile robots.

Collision avoidance system for aircraft ground operations

Abstract: A ground collision avoidance system (GCAS) for an aircraft is disclosed. A radio frequency (RF) sensor senses a location of an obstacle with respect to the aircraft moving along the ground. An expected location of the obstacle with respect to the aircraft is determined from the sensed location and a trajectory of the aircraft. An alarm signal is generated when the expected location of the obstacle is less than a selected criterion.

Information display system and information display device

Abstract: There is provided an information display system for supporting a high safety driving, so that a driver can clearly recognize an obstacle. A shape of a virtual image indicating an outline or a frame line of the obstacle is changed according to a risk level of the obstacle against a vehicle, and a display position of the virtual image is adjusted according to a viewpoint position of the driver, so that a deviation in displaying between an actual obstacle and the virtual image is suppressed. In addition, there is provided an information display system which can make the driver intuitively recognize the obstacle without hindering the driving by displaying an estimated traffic line of the obstacle as the virtual image.

Object detection and obstacle avoidance for mobile robot using stereo camera

Abstract: The objective of this research is to develop a real time obstacle detection and obstacle avoidance for autonomous navigation of mobile robots using a stereo camera in an unstructured environment. Autonomous navigation of mobile robots demands a) Exact determination of position and orientation of Robot and b) Accurate determination of size, shape, depth and range of potential obstacles in the environment. Simple kinematic model is used for mobile robot and stereo camera with pan and tilt provision is considered for long range operation. Complete 3D reconstruction of object/obstacle is obtained from the stereo matching algorithm and with triangulation method. The pose (position and orientation) of mobile robot is formulated from the static object observation with stereo reference matching points using RANSAC (RANdom SAmple Consensus) in successive frames. Potential field based obstacle avoidance formulation is carried out by using the obstacle range, size information, mobile robot position and orientation. Finally, proportional derivative navigation control loop along with obstacle avoidance algorithm is formulated and verified.

Online obstacle avoidance at high speeds

Abstract: This paper presents an efficient algorithm for online avoidance of static obstacles that accounts for robot dynamics and actuator constraints. The robot trajectory (path and speed) is generated incrementally by avoiding obstacles optimally one at a time, thus reducing the original problem from one that avoids m obstacles to m simpler problems that avoid one obstacle each. The computational complexity of this planner is therefore linear in the number of obstacles, instead of the typical exponential complexity of traditional geometric planners. This approach is quite general and applicable to any cost function and to any robot dynamics; it is treated here for minimum time motions, a planar point mass robot, and circular obstacles. Numerical experiments demonstrate the algorithm for very cluttered environments (70 obstacles) and narrow passages. Upper and lower bounds on the motion time and on the path length were derived as functions of the Euclidean distance between the end points and the average obstacle size. Comparing a kinematic version of this algorithm to the RRT and RRT* planners showed significant advantages over both planners. The algorithm was demonstrated on an experimental mobile robot moving at high speeds in a known environment.