Showing papers on "Obstacle avoidance published in 1990"

Real-time obstacle avoidance for manipulators and mobile robots

Abstract: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to move in a straight line with an...

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. >

Manipulator control with superquadric artificial potential functions: theory and experiments

Abstract: A potential function based on superquadrics is presented that closely models a large class of object shapes. This potential function also prevents the creation of local minima when it is added to spherically symmetric attractive wells. Two compatible forms of the superquadric potential function are introduced: one for obstacle avoidance, and another for obstacle approach. The avoidance and approach potentials are implemented in simulations. In these simulations the end effector of the manipulator experiences an attractive force from a global spherical well, while the end effector and each of the links experience repulsive forces from all of the objects. The authors have also experimentally implemented the avoidance potentials on the CMU DDARM II system. The results demonstrate successful obstacle avoidance and approach, and exhibit an improvement over existing schemes. >

An obstacle avoidance algorithm for hyper-redundant manipulators

Abstract: Novel kinematic algorithms for implementing planar hyperredundant manipulator obstacle avoidance is presented. Unlike artificial potential field methods, the method outlined is strictly geometric. Tunnels are defined in a workspace in which obstacles are presented. Methods of differential geometry are then used to formulate equations which guarantee that sections of the manipulator are confined to the tunnels and therefore avoid the obstacles. A general formulation is given with examples to illustrate this approach. >

Local obstacle avoidance for mobile robots based on the method of artificial potentials

Abstract: In the method of artificial potentials, the robot behaves like a charged particle that is attracted by the goal position and repelled by the obstacles. An overview of the method is presented which describes the common variations in a unified framework, compares the performances of the different algorithms, and corrects some common misunderstandings. It is shown that force control algorithms with generalized potentials (which depend on velocity as well as position) offer advantages over other alternatives. Also discussed are the problems of stability and convergence. >

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.

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. >

Tether-guided vehicle and method of controlling same

Abstract: A tether-guided vehicle and method of controlling same are disclosed. A tether sensor indicates the angle, ϑ, of the tether with respect to the vehicle and the tension, T, on the tether. A contact-sensitive bumper disposed about at least the front periphery of the vehicle indicates the position, P, and force, F, of contact with an obstacle. A drive system moves the vehicle in response to tether angle, ϑ, and tension, T, thereby providing a "servo pull" feature. When the vehicle contacts an obstacle, it stops, backs up, turns and resumes forward motion to circumnavigate the obstacle, thereby providing an "obstacle avoidance" feature. The invention automatically frees a tether-guided vehicle from a jammed condition. It also improves the maneuverability of tether-guided vehicles. The servo pull and obstacle avoidance features make the vehicle suitable in a number of applications, such as for canister vacuums, hospital or factory carts, and the like. The vehicle may be tethered to another robotic vehicle.

Coping with uncertainty in a control system for navigation and exploration

Abstract: A significant problem in designing mobile robot control systems involves coping with the uncertainty that arises in moving about in an unknown or partially unknown environment and relying on noisy or ambiguous sensor data to acquire knowledge about that environment. We describe a control system that chooses what activity to engage in next on the basis of expectations about how the information returned as a result of a given activity will improve its knowledge about the spatial layout of its environment. Certain of the higher-level components of the control system are specified in terms of probabilistic decision models whose output is used to mediate the behavior of lower-level control components responsible for movement and sensing. The control system is capable of directing the behavior of the robot in the exploration and mapping of its environment, while attending to the real-time requirements of navigation and obstacle avoidance.

Visual Guidance Of A Mobile Robot Equipped With A Network Of Self-Motion Sensors

Abstract: This paper reports on the principles of an on-board electro-optical system for the guidance of an autonomous mobile robot. Some of the signal processing adopted here was directly inspired by natural visual systems, in particular by the compound eye of the fly. The visual system has compound optics with a panoramic field but relatively low spatial resolution. It makes use of elementary motion detectors (E.M.D's) to estimate the distance to objects from the optic flow. Each E.M.D. constitutes one mesh of an analog network. It measures the relative angular velocity of any contrast point that passes across its receptive field as a result of the robot's own motion and evaluates the radial distance to this contrast point from the motion parallax. For this purpose, the mobile makes translation steps at constant speed during each visual acquisition. An obstacle avoidance algorithm is implemented on a parallel, analog network. This network integrates the numerous data provided by the E.M.D's and controls the drive motor and steering motor of the robot platform in real time. Other navigation modules may be added without altering the basic hardware architecture of the system. For example, a target detector has been associated with the system. No stringent hypothesis needs to be made as to the shape of objects in the environment. Both the visual processing principles and the obstacle avoidance strategy are described.

A motion planner for car-like robots based on a mixed global/local approach

Abstract: Deals with the problem of motion planning for a car-like robot (i.e. nonholonomic mobile robot whose turning radius is lower bounded). The main contribution is the introduction of a new metric in the configuration space R/sup 2/*S/sup 1/ of such a system. This metric is defined from the length of the shortest paths in the absence of obstacles. The authors study the relations between the new induced topology and the classical one. This study leads to new theoretical issues about sub-Riemannian geometry and to practical results for motion planning. In particular they prove an inclusion relation of neighbourhoods in both topologies, which is the basis of an efficient obstacle avoidance local method. >

An opportunistic global path planner

Abstract: A robot planning algorithm that constructs a global skeleton of free-space by incremental local methods is described. The curves of the skeleton are the loci of maxima of an artificial potential field that is directly proportional to the distance of the robot from obstacles. The method has the advantage of fast convergence of local methods in uncluttered environments, but it also has a deterministic and efficient method of escaping local extremal points of the potential function. The authors present a general algorithm, for configuration spaces of any dimension, and describe instantiations of the algorithm for robots with two and three degrees of freedom. >

Reflexive teleoperated control system for a remotely controlled vehicle

Abstract: A control system for a remotely controlled vehicle comprises a supervisory control system which receives supervisory speed and turn rate commands from a human operator which are provided to a servo-controlled vehicle; an obstruction detection system having multiple sensors mounted to the vehicle detect any obstructions in the path of the vehicle; and a collision avoidance control system coupled to the supervisory control system, the obstruction detection system, and to the vehicle The collision avoidance control system disables the supervisory speed and turn rate commands when the obstruction detection system detects an obstruction The collision avoidance control system also generates and provides obstacle avoidance speed and turn rate commands to the vehicle to direct the vehicle to avoid obstruction in the path of the vehicle, and enables the supervisory speed and turn rate commands after the obstruction is avoided so that control of the vehicle is returned to the human operator The magnitude of the obstacle avoidance speed command is proportional to a first distance between one of the sensors detecting the obstruction and the obstruction itself when the first distance is within a first predetermined limit; and the magnitude of the turn rate command is inversely proportional to an angle defined between an operator desired vehicle heading and a relative bearing to the detected obstruction when the obstruction is within a second distance from the vehicle

Joint trajectory generation for redundant robots in an environment with obstacles

Abstract: The problem of determining collision-free joint space trajectories for redundant robots is considered, and the command-generator approach is used to generate such trajectories. In this approach, a distance objective function is defined and is optimized along the robot joint trajectories through a vector in a null space. Algorithms for implementing this optimization problem are fully developed. It is shown that the proposed collision-free trajectory generation scheme is efficient and practical. Extensive simulation results of a four-link robot example are presented and analyzed. >

A stereo vision system for real time obstacle avoidance in unknown environment

Abstract: A stereo vision system for detecting and avoiding obstacles in real time in an unknown environment is described. This is only the low level of the control system architecture of a mobile robot based on the Brook's subsumption architecture. This level is based on a stereo vision algorithm that uses precomputed measurement of the ground floor disparity, and online acquired grey-level stereo images. The floor is supposed to be planar. The algorithm has been successfully implemented on a mobile vehicle, that is capable of moving around in an unpredictable environment, like a laboratory, without collision. >

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. >

Multi-criteria position and configuration optimization for redundant platform/manipulator systems

Abstract: An important characteristic of practical mobile manipulators, i.e. manipulators mounted on mobile platforms, is their particular kinematic redundancy created by the addition of the degrees of freedom of the platform to those of the manipulator. This paper is concerned with the resolution of this kinematic redundancy, and in particular with the local optimization of the position and configuration of the system during task commutations when changes occur in both task requirements and task constraints. Optimization criteria for obstacle avoidance, manipulability, least torque norm and maximum actuator torque are first discussed. Emphasis is then placed on optimization methods for problems involving multi-requirements and multicriteria optimization. Sample results of the methods for a system including a three-link manipulator mounted on a mobile platform are presented and discussed. >

Inertial navigation sensor integrated motion analysis for obstacle detection

Abstract: A maximally passive approach to obstacle detection is described, and the details of an inertial sensor integrated optical flow analysis technique are discussed. The optical flow algorithm has been used to generate range samples using both synthetic data and real data (imagery and inertial navigation system information) obtained from a moving vehicle. The conditions under which the data were created/collected are described, and images illustrating the results of the major steps in the optical flow algorithm are provided. >

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

Towards a real-time architecture for obstacle avoidance and path planning in mobile robots

Abstract: The design and partial implementation of a real-time architecture for a mobile robot, aimed particularly towards a vehicle developed for factory automation, is described. The authors develop a layered design to equip the robot with a number of behavioral competences. They examine sensing and a potential field algorithm especially to achieve modification of behavior at a speed close to the robot's operational speed. It is shown how the layered architecture interfaces to the original onboard architecture, which provided sophisticated localization but no ability to deal with environmental exceptions. >

Trajectory generation for cooperating robots

Abstract: A formulation for online trajectory generation for two robots cooperating to perform an assembly task is derived. The two robots are treated as a single redundant system. A Jacobian is formulated that relates the joint rates of the entire system to the relative motion of one of the hands with respect to the other. The minimum norm solution of this relative Jacobian equation results in a set of joint rates which perform the cooperative task. In addition to the cooperative task, secondary goals, which include obstacle and joint limit avoidance, are specified using velocities in the null space of the relative Jacobian. This formulation also allows the robots to be controlled in parallel on independent tasks

Concept development of automatic guidance for rotorcraft obstacle avoidance

Abstract: The automatic guidance of rotorcraft for obstacle avoidance in nap-of-the-earth flight is studied. The author considers a hierarchical breakdown of the guidance components to identify the functional requirements. These requirements and anticipated sensor capabilities lead to a preliminary guidance concept, which has been evaluated via computer simulations. >

An efficient local approach for the path generation of robot manipulators

Abstract: In this article an efficient local approach for the path generation of robot manipulators is presented. The approach is based on formulating a simple nonlinear programming problem. This problem is considered as a minimization of energy with given robot kinematics and subject to the robot requirements and a singularities avoidance constraint. From this formulation a closed form solution is derived which has the properties that allows to pursue both singularities and obstacle avoidance simultaneously; and that it can incorporate global information. These properties enable the accomplishment of the important task that while a specified trajectory in the operational space can be closely followed, also a desired joint configuration can be attained accurately at a given time. Although the proposed approach is primarily developed for redundant manipulators, its application to nonredundant manipulators is examplified by considering a particular commercial manipulator.

Robotic end effector for handling greenhouse plant material.

Abstract: An end effector was developed to investigate the mechanics and control of robotic handling and manipulation of plant material of a type commonly found in commercial greenhouses. The end effector was shown to handle a wide range of sizes of geranium cuttings with rare indications of damage to the petioles (1.5%) and main stem (2.0%). Several features of the end effector were determined to be important for reliable, non-damaging performance. A two-stage feedback controller which combined position/velocity control with force control was successful in minimizing cycle time while also minimizing impact velocity and resultant impact loads on plant material. A machine vision local scene analysis technique provided an automatic method of obstacle avoidance by the fingers in a plant canopy. Padded fingers with relatively small, curved ends minimized contact area and assisted in decreasing impact forces. In general, results indicate the importance of sensing and interpretation of the sensor data to assist a robot in accommodating the nonuniformity typical of plants.

Sensor-based control of AGVs

Abstract: This article summarises work on a number of related sensor-guided mobile robot projects at Oxford University. Two fundamental problems are discussed: navigation and obstacle avoidance. Beacons are central to navigation. Implemented systems are described that make different assumptions about the environment and use different beacons. An implemented system is also described that can sense and avoid obstacles on the fly, without stopping. It is based on a layered architecture. A fully decentralised Kalman filter has been applied to a number of sensor integration tasks, including tracking an object visually as it moves around a room.

Modeling the Environment of a Mobile Security Robot

Abstract: : ROBART II is a battery powered autonomous robot being used by the Naval Ocean Systems Center (NOSC) in San Diego, CA as a testbed in research which seeks to provide a multisensor detection, verification, and intelligent assessment capability for a mobile security robot. The intent is to produce a robust automated system exhibiting a high probability of detection, with the ability to distinguish between actual and nuisance alarms, and capable of operation within areas already protected by fixed installation motion detection sensors. An architecture of 13 distributed microprocessors onboard the robot makes possible advanced control strategies and realtime data acquisition. Higher-level tasks (map generation, path planning, position estimation, obstacle avoidance, and statistical security assessment) are addressed by a Planner (currently a remote 80386-based desktop computer). Numerous sensors are incorporated into the system to yield appropriate information for use in position estimation, collision avoidance, navigational planning, and assessing terrain traversibility.

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. >

An approach to obstacle recognition for autonomous mobile robots

Abstract: Dynamic vision may be utilized for detecting and classifying objects that could be obstacles for a mobile robot. Methods for accomplishing this are introduced. They have been implemented on a multiprocessor vision system and tested in outdoor environments. If conditions are fairly favorable obstacles are reliably recognized and false alarms (e.g. caused by shadows) are rejected. Among the main problems which have not yet been completely solved are the tracking of the road in a great distance, the recognition of the contours of an object when many features are visible on the object's surface, and the separation of the object from the background. >