Showing papers on "Obstacle published in 1990"

Real-time obstacle avoidance for fast mobile robots in cluttered environments

Abstract: The method described, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. A VFH-controlled mobile robot maneuvers quickly and without stopping among densely cluttered obstacles. The VFH method uses a two-dimensional Cartesian histogram grid as a world model. This world model is updated continuously and in real time with range data sampled by the onboard ultrasonic range sensors. Based on the accumulated environmental data, the VFH method then computes a one-dimensional polar histogram that is constructed around the robot's momentary location. Each sector in the polar histogram holds the polar obstacle density in that direction. Finally, the algorithm selects the most suitable sector from among all polar histogram sectors with low obstacle density, and the steering of the robot is aligned with that direction. Experimental results from a mobile robot traversing a densely cluttered obstacle course at an average speed of 0.7 m/s demonstrate the power of the VFH method. >

Obstacle avoidance for redundant robots using configuration control

Abstract: A redundant robot control scheme is provided for avoiding obstacles in a workspace during motion of an end effector along a preselected trajectory by stopping motion of the critical point on the robot closest to the obstacle when the distance therebetween is reduced to a predetermined sphere of influence surrounding the obstacle. Algorithms are provided for conveniently determining the critical point and critical distance.

Inertial navigation sensor integrated obstacle detection system

Abstract: A system that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system is a maximally passive obstacle detection system that makes selective use of an active sensor. The active detection typically utilizes a laser. Passive sensor suite includes binocular stereo, motion stereo and variable fields-of-view. Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.

Teleautonomous guidance for mobile robots

Abstract: A novel technique for the remote guidance of fast mobile robots has been developed and implemented. With this method, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This novel implementation of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. The method, called teleautonomous operation, allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. Teleautonomous operation is based on the virtual force field (VFF) method, which was developed for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles. >

A new path planning algorithm for moving a point object amidst unknown obstacles in a plane

Abstract: A nonheuristic path planning for moving a point object, or mobile automation (MA), in a two-dimensional plane, amidst unknown obstacles, is considered. A path is to be generated, point by point, using only the local information, like the MA's current position and whether it is in contact with an obstacle. A path-planning algorithm to solve this problem is proposed. The algorithm is used to realize the smallest worst-case path length possible in its category. The procedure for the algorithm is presented with explanations. Its various characteristics, such as local cycle creation, worst-case path length, target reachability conditions, etc. are dealt with. Its performance is compared with that of the existing algorithms. Examples showing the operation of the algorithm are presented. >

A unified approach for robot motion planning with moving polyhedral obstacles

Abstract: A unified approach suitable for path planning with moving polyhedral obstacles is presented. The planner views the space-time configuration of free space as disjoint polytopes that represent a time-dependent environment consisting of moving and stationary objects. Each point in the space-time domain is mapped into a unique polytope set. The planner then constructs a family of feasible collision-free trajectories by searching connected polytopes between the start polytope and the goal polytope that satisfy the speed and time constraints. Finally, a near-optimal trajectory is determined by constrained optimization. This approach does not require that obstacles be nonoverlapping or noncolliding. In addition, the obstacle is allowed to move faster than the planned robot. However, the speed of the obstacle must be piecewise-constant. The proposed approach can be easily extended to motion planning in higher dimensional spaces. >

Visual obstacle detection for automatically guided vehicles

Abstract: A stereo obstacle detection system has been developed for automatically guided vehicles that operate on flat (factory) floors. The system does not attempt to reconstruct the 3D environment visually but simply tries to detect obstacles on the floor in the vehicle's path. The approach to stereo image processing uses inverse perspective mappings to facilitate matching of the binocular field of vision against the expected 3D structure of the environment. Assuming a known relative camera model, a geometrical image transformation is computed which essentially compensates the stereo disparities for the image points of the floor. After the mapping operation the images are compared and local mismatches are interpreted as possible obstacle locations. The system has been successfully tested in a factory environment. The implementation runs on standard microprocessor hardware in real time. >

Application of multi-target tracking to sonar-based mobile robot navigation

Abstract: The authors describe an approach to mobile robot navigation that unifies the problems of obstacle avoidance, position estimation, and map building in a common multi-target tracking framework. Model-based navigation is viewed as a process of tracking naturally occurring geometric targets or beacons. Targets that have been predicted (expected) from the environment map are tracked to provide vehicle position estimates (localization). Targets that are observed, but not predicted, represent unknown environment features or obstacles and cause new tracks to be initiated, classified, and ultimately integrated into the map. A good sensor model is a crucial component of this approach, and is used both for predicting expected observations and classifying unexpected observations. This navigation framework is being implemented on a mobile robot that employs sonar as the principal navigation sensor. An implementation of model-based localization that achieves robust position estimation in a known environment is presented. Preliminary results in obstacle identification and map building are given that lead one to believe that a complete navigation system, encompassing localization, obstacle avoidance, and map building, can be implemented exclusively with sonar. >

Implementation of dynamic obstacle avoidance on the CMU NavLab

Abstract: The design and implementation of local obstacle avoidance algorithms on the CMU NavLab testbed for autonomous navigation are presented. The CMU NavLab carries various computing systems, including three Suns, one Warp systolic array processor, and several Intel 386 real-time processors, for the purpose of processing sensor information and generating vehicle motion commands. The obstacle avoidance algorithm presented is part of a reflexive path tracking scheme. To handle such situations where obstacles are present on the predefined path, an obstacle avoidance algorithm is added to the reflexive path tracking scheme whereby when an obstacle is detected on the predefined path, the vehicle control is transferred to the obstacle avoidance algorithm which guides the vehicle around the obstacle. This combination results in a scheme that reacts to the changing and uncertain environment. A subgoal selection algorithm and a steering control algorithm are also discussed

Obstacle detection by evaluation of optical flow fields

Abstract: A blood sampling assembly is provided which has a cannula designed for intravenous penetration, a mechanism for applying negative pressure to the cannula, a chamber located between the cannula and the source of negative pressure, a one-way valve positioned within the chamber, and a venting member within the chamber which allows the venting of air as blood enters the chamber, but does not allow the passage of blood. A person drawing blood is enabled to visually determine when a needle is properly inside a vein through transparent walls of the chamber. Spillage of blood is avoided with the present assembly by the resistance of the one-way valve to flow distally from the intravenous cannula.

Obstacle detection system

Abstract: A system (10) that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system (10) is a maximally passive obstacle detection system that makes selective use of an active sensor (52). The active detection (52) typically utilizes a laser. Passive sensor suite includes binocular stereo (54), motion stereo (56) and variable fields-of-view (57). Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.

Obstacle avoidance using neural networks

Abstract: A neural network that limits the closest point of approach of an autonomous underwater vehicle (AUV) with respect to a navigation obstacle is described. Neural network inputs consist of beam outputs from a forward-looking sonar, and differences between current and desired values for AUV course and speed are inputs to normal navigation and control. The neural network outputs are AUV rudder angle and propulsion power: basic vehicle maneuvering characteristics are incorporated in the model. Obstacle avoidance is accomplished using a proximity detector for avoiding static obstacles and a rate detector for avoiding moving obstacles. The detections are made using 2D masked binary filters implemented as multilayer neural networks in the classification mode. Adaptive training is not used: instead. neuron weights are defined by the desired AUV response. The AUV simulation successfully avoided collision with all obstacles during test runs. >

Crossing obstructing detector

Abstract: PROBLEM TO BE SOLVED: To positively detect an obstacle in a grade crossing by determining size and movement of an object without newly providing wiring or conduit piping. SOLUTION: When crossing gate rods 7 and 8 start to descend, a distance sensor 3 rotates right and left within a detection area in the grade crossing, emits a laser beam, and searches for an obstacle in the grade crossing. The distance sensor 3 checks deviation of a rotating azimuth and send and receive performances by reflected light from a reflector 4. When the laser beam of the distance sensor 3 moves the azimuth, azimuth information and distance information of a passer 9 are collected, they are compared with azimuth information and distance information stored in an information processing part inside a grade crossing apparatus box 1, and it is determined that the passer 9 is an obstacle. Furthermore, the laser beam moves the azimuth and azimuth information and distance information of a plurality of portions of an automobile 10 are collected. The information processing part inside the grade crossing apparatus box 1 traces a measured shape from the plural pieces of azimuth information and distance information, judges that the object is the automobile 10 form a stored shape, and determines that it is an obstacle.

Establishing collision zones for obstacles moving with uncertainty

Abstract: This paper presents a methodology to include obstacles moving with uncertainty in path planning algorithms. Around each moving obstacle, a collision zone is defined indicating a high collision likelihood space. These zones are treated as stationary obstacles providing the input to a path planning algorithm. Samples of moving obstacles' positions are assumed to be available. Three models of motion for moving obstacles are considered: (1) obstacles moving randomly, (2) obstacles whose motion is structured but consists of random parameters, (3) obstacles whose motion is predictable as a function of time. Simulation examples yielding collision zones are presented.

A collision avoidance controller for autonomous underwater vehicles

Abstract: A 3D collision avoidance controller for an autonomous underwater vehicle (AUV) that uses a forward-looking high-frequency active sonar is described. Multiple objects are differentiated by clustering sonar returns, and Kalman filters are then used to track both stationary and moving obstacles. A minimum safe distance must be maintained between the AUV and any obstacle, and a modified potential field is used to determine appropriate maneuvers. The merit function which defines this potential field is based on obstacle bearing, distance, and visit count, as well as the AUV heading, the depth, and the direction of the goal. >

Roads, rivers, and obstacles: optimal two-dimensional path planning around linear features for a mobile agent

Abstract: This paper appeared in International Journal of Robotics Research, 9, no. 6 (December 1990), pp. 67-74. Equations were redrawn in 2008.

A stochastic algorithm for obstacle motion prediction in visual guidance of robot motion

Abstract: The algorithm presented is based on a hidden Markov model description of the motions of obstacles and uses probabilistic evaluation for the selection of collision-free trajectories in the visual guidance of mobile robot motion. The algorithm is reliable in terms of catching the nature of obstacle motions in a dynamic environment. The computation time is modest, as the simulation results show

Flow past cylindrical obstacles on a beta-plane

Abstract: The flow past a cylindrical obstacle in an enclosed channel is examined when the entire configuration is rotating rapidly about an axis which is aligned with that of the obstacle. When viewed from a frame of reference which is rotating with the channel, Coriolis forces dominate and act to constrain the motion to be two-dimensional. The channel is considered to have depth varying linearly across its width, producing effects equivalent to the so-called-beta-plane approximation and permitting waves to travel away from the obstacle, both upstream and downstream. For the eastward flow considered in this paper, this leads to the formation of a lee-wavetrain downstream of the obstacle and, under some conditions, a region of retarded, or 'blocked', flow upstream of the obstacle. The flow regime studied is essentially inviscid, although one form of frictional effect on the flow, introduced through the Ekman layers, is included. The properties of this system are examined numerically and compared with the theoretical predictions from other studies, which are applicable in asymptotic limits of the parameters. In particular, the relevance of 'Long's model' solutions is considered.

Parameterized descriptions of the joint space obstacles for a 5R closed chain robot

Abstract: An examination is made of the equations for the boundaries of the joint-space obstacles in the workspace of a 5R closed-chain robot. This two-degree-of-freedom chain appears in many robotics applications. The equations describing the joint-space obstacle boundaries are derived, using three different sets of parameters, and the obstacles are graphically displayed. The boundaries of polygonal obstacles in contact with the polygonal links of a robot arm are studied using the 4D image space of planar displacements. The obstacles are mapped into the image space as the surface representing the position and orientation that a body assumes while maintaining contact with the obstacle. The intersection of the available robot positions and the obstacle contact positions is a representation of the obstacles in the robot's workspace. Three parameterizations of joint-space obstacles are determined from the image-space representation: the joint angles of one of the 2R robots, the end effector position, and the base joint angles of the 5R chain. The first and third parameter sets define two possible configurations for the 5R chain, and the second defines four possible configurations. >

Dynamic digital distance maps in two dimensions

Abstract: An efficient means for dealing with obstacles in motion is provided to extend the usefulness of digital distance maps. An algorithm is presented that allows one to compute what portions of a map will probably be affected by an obstacle's motion. The algorithm is based on an analysis of the distance transform as a problem in wave propagation. The regions that must be checked for possible updates when an obstacle moves are those that are in its or in the shadow of obstacles that are partially in the shadow of the moving obstacle. The technique can handle multiple fixed goals, multiple obstacles moving and interacting in an arbitrary fashion, and it is independent of the technique used for calculation of the distance map. The algorithm is demonstrated on a number of synthetic two-dimensional examples, and example timing results are reported. >

An Intelligent Path Planning System for Robot Navigation in an Unknown Environment

Abstract: In this paper, a novel approach to solve the mobile robot path planning problem in an unknown environment is presented. Inherently, the obstacle information from robot perception is contaminated with uncertainties, and thus, the acquired obstacle knowledge for path planning needs to be updated dynamically. Therefore, the development of an adaptive path planning scheme capable of determining a desired path with uncertain, and incomplete obstacle knowledge is necessary. We use the concept of traversability vectors to analyze the spatial-relations between the robot and obstacles in the task environment. Then, these analyzed relations are used to determine the obstacles that must be bypassed by the robot, and the ways to bypass them. Dynamically changing obstacle knowledge can be accommodated by replanning the path at the time when a change is reported. The proposed scheme can work very efficiently since because of the elimination of an exhausted search process that is often required in previous approaches. We implement a computer program to simulated the proposed planning scheme. A graphical representation for robot motions guided by the planned paths is illustrated to show the feature of the presented work.

AUV control using geometric constraint-based reasoning

Abstract: The geometric constraint approach to motion planning with moving obstacles for autonomous underwater vehicles (AUVs) is reviewed. The authors discuss how constraints for optimizing sensor operation, nonuniform obstacle avoidance and predictable nonlinear obstacle motion can be generated by the system. The process of generating and combining the following diverse constraint types is explained: sensor orientation; flow noise; self noise; and droop avoidance; nonuniform obstacle avoidance; and predictable nonlinear obstacle motion. This method allows motion constraint descriptions using any number of separate speed and direction components, and provides a flexible means of controlling their subsequent combination. >

Flow of a liquid-crystalline polymer solution around an obstacle

Abstract: The behaviour of an anisotropic solution of hydroxypropylcellulose around an obstacle is investigated in shear and during relaxation. Experiments were carried out with an optical rheometer equipped with transparent cone-and-plate. The obstacle is a 200 micron glass sphere stuck on the plate. A typical Reynolds number past the obstacle is about 10−5. The flow of the anisotropic solution perturbed by the obstacle shows specific phenomena: distorted downstream streamlines, a very long wake behind the obstacle during shear which persists a long time after the ceasing shear, a change in the behaviour at very high shear rates and in particular, the appearance of a wake in front of the obstacle. To date there has not been any theoretical bases with which to explain these new findings. An interesting point is that the wake behind the obstacle is a good illustration of the problem of weldlines in injection moulding.

Monotone iterations for nonlinear obstacle problem

Abstract: The existence, uniqueness and regularity of solutions are proved for the obstacle problem with semilinear elliptic partial differential equations of second order. Computationally effective algorithms are provided and application made to steady state problem for the logistic population model with diffusion and an obstacle to growth.

Anti-collision system for motor car

Abstract: PURPOSE:To prevent collision effectively by producing a brake operation signal, when the processing results of detection signal of an obstacle sensor mounted on an electric automobile matches with predetermined conditions, thereby exerting a brake force onto a motor. CONSTITUTION:Output of power supplies 16, 17 are controlled by means of motor drivers 181-192, based on a command fed from a controller 15, to drive motors 131-142 individually and the rotational speeds thereof are fed to the controller 15 through a resolver (not shown). The controller 15 is provided with an obstacle sensor 30 in addition to conventional speed sensor 31, a steering angle sensor 32, a drive/reverse indication switch 33, an accelerator opening sensor 34 and a brake sensor 35. When the obstacle sensor 30 detects an obstacle, the controller 15 operates the direction and the distance of the obstacle and then exert brake force onto the motors 131-142 thus steering the motor car. According to the constitution, an against an object can be avoided effectively.

A comparison of two obstacle avoidance path planners for autonomous underwater vehicles

Abstract: The breadth-first path planner is compared to the optimal A* path planner in terms of distance traveled and computation time. Certain modifications are added to the obstacle avoidance algorithm to increase its robustness to vehicle position uncertainties arising from the Doppler/INS system. Simulation results show that the A* path planner generates paths that are between 0.8 and 1.1 times the length of the paths generated by the breadth-first approach. Computationally, however, the A* solution takes anywhere from 1.5 to 19.8 times longer to calculate. Repeated trials in simulated, dense obstacle fields have verified that despite position uncertainties, the obstacle avoidance algorithm safely guides an autonomous underwater vehicle along a planned path to the desired end point. >