Showing papers on "Obstacle avoidance published in 1995"

Error eliminating rapid ultrasonic firing for mobile robot obstacle avoidance

Abstract: This paper introduces error eliminating rapid ultrasonic firing (EERUF), a new method for firing multiple ultrasonic sensors in mobile robot applications. EERUF allows ultrasonic sensors to fire at rates that are five to ten times faster than those customary in conventional applications. This is possible because EERUF reduces the number of erroneous readings due to ultrasonic noise by one to two orders of magnitude. While faster firing rates improve the reliability and robustness of mobile robot obstacle avoidance and are necessary for safe travel at higher speed (e.g., V>0.3 m/sec), they introduce more ultrasonic noise and increase the occurrence rate of crosstalk. However, EERUF almost eliminates crosstalk, making fast firing feasible. Furthermore, ERRUF's unique noise rejection capability allows multiple mobile robots to collaborate in the same environment, even if their ultrasonic sensors operate at the same frequencies. The authors have implemented and tested the EERUF method on a mobile robot and they present experimental results. With EERUF, a mobile robot was able to traverse an obstacle course of densely spaced, pencil-thin (8 mm-diameter) poles at up to 1 m/sec. >

Vehicle surroundings monitor with obstacle avoidance lighting

Abstract: The vehicle surroundings monitor detects the sizes and positions of obstacles, ditches and humans as well as the depths of the ditches to provide the driver with sufficient information to secure safety during driving. The pattern light projector receives an incoming laser beam and projects a light spot matrix in the form of a regular grating onto the monitored area. The camera photographs the light spot pattern on the monitored area and sends image signals to the data processor which processes the image signals to detect the presence of any obstacle, ditch or human. Based on the steering angle detected by the steering angle sensor, the path the car will take is predicted and a possible contact or collision of the car with the obstacle is detected beforehand. The buzzer, voice synthesizer and display device are used to alert the driver and indicate the presence of the obstacles, the possible contact with them and the location where the possible contact will occur.

Fuzzy Logic Wall Following of a Mobile Robot Based on the Concept of General Perception

Abstract: This paper presents a new approach to the wall following problem of a mobile robot. Local path planning is based on a so-called concept of general perception, which means that the robot is guided by a representation of its perception only. No map of the environment is used and walls and obstacles are not modelled either. A fuzzy controller then uses the information provided by the concept of general perception to guide the robot along walls of arbitrary shape and around obstacles which are treated as part of a wall, unless the distance between obstacle and wall allows a safe passage. This paper first introduces the concept of general perception and then explains the fuzzy controller in detail. All membership functions and the complete rule base are provided. The concept of general perception together with the fuzzy controller were tested on a real robot performing wall following and obstacle avoidance missions and some of the ensuing experimental results are presented at the end of the paper.

Real-time collision avoidance for redundant manipulators

Abstract: This paper presents a simple and robust approach to achieving collision avoidance for kinematically redundant manipulators at the control-loop level. The proposed scheme represents the obstacle avoidance requirement as inequality constraints in the manipulator workspace, and ensures that these inequalities are satisfied while the end-effector tracks the desired trajectory. The control scheme is the damped-least-squares formulation of the configuration control approach implemented as a kinematic controller. Computer simulation and experimental results are given for a Robotics Research 7 DOF redundant arm and demonstrate the collision avoidance capability for reaching inside a truss structure. These results confirm that the proposed approach provides a simple and effective method for real-time collision avoidance. >

Experience with rover navigation for lunar-like terrains

Abstract: Reliable navigation is critical for a lunar rover, both for autonomous traverses and safeguarded remote teleoperation. This paper describes an implemented system that has autonomously driven a prototype wheeled lunar rover over a kilometer in natural, outdoor terrain. The navigation system uses stereo terrain maps to perform local obstacle avoidance, and arbitrates steering recommendations from both the user and the rover. The paper describes the system architecture, each of the major components, and the experimental results to date.

Neuropsychological Predictors of Complex Obstacle Avoidance in Healthy Older Adults

Abstract: Global cognitive impairment in older adults has been associated with a greater risk of falling, and tripping has been implicated as an important factor in a large percentage of these falls. In order to evaluate the role of specific cognitive domains in tripping and falling, 23 healthy older adults completed basic and complex obstacle avoidance tasks, as well as a battery of neuropsychological tests. Using multiple regression analysis, a select pattern of neuropsychological measures was found to predict the decrement in performance evident as avoidance task complexity increased. Whereas measures of problem solving, response inhibition, general anxiety, and variability in attention were found to be significant predictors (in that order) of the relative decline in successful obstacle avoidance, measures of visuo-spatial discrimination and memory did not.

Fusion of human and machine intelligence for telerobotic systems

Abstract: A new intelligent fusion scheme for human operator command and autonomous planner/controller in telerobotic system has been developed based on the event-based planning and control theory. It provides a unified model to integrate a human operator control command with action planning and control of autonomous operation. As a result, the telerobotic system can perform tasks which cannot be done by either human operator or autonomous planner/controller alone. This scheme lays down a foundation for planning and control of a general robotic system involving human operators, and provides a natural and efficient way to fuse the human intelligence with the machine intelligence. The scheme is implemented and tested on a PUMA 560 robotic system. The experimental results of obstacle avoidance, and hybrid force/position control with a commanded force are presented.

Trajectory generation for obstacle avoidance of uncalibrated stereo visual servoing without 3D reconstruction

Abstract: In this paper, a trajectory generator for a visual servoing system is proposed to make the system accomplish obstacle avoidance tasks in unknown environments. Using an estimated epipolar constraint, the proposed scheme can generate trajectories for the visual servoing system on the 2D image planes by a simple obstacle avoidance method without reconstructing 3D geometry. The proposed scheme is based on the idea, "as long as one of the projected trajectories does not intersect with projected obstacles, the trajectory in 3D space can avoid the obstacles". An experimental result is shown to demonstrate the validity of a combination of the proposed trajectory generator and the visual servoing control scheme.

Active/dynamic stereo vision

Abstract: Visual navigation is a challenging issue in automated robot control. In many robot applications, like object manipulation in hazardous environments or autonomous locomotion, it is necessary to automatically detect and avoid obstacles while planning a safe trajectory. In this context the detection of corridors of free space along the robot trajectory is a very important capability which requires nontrivial visual processing. In most cases it is possible to take advantage of the active control of the cameras. In this paper we propose a cooperative schema in which motion and stereo vision are used to infer scene structure and determine free space areas. Binocular disparity, computed on several stereo images over time, is combined with optical flow from the same sequence to obtain a relative-depth map of the scene. Both the time to impact and depth scaled by the distance of the camera from the fixation point in space are considered as good, relative measurements which are based on the viewer, but centered on the environment. The need for calibrated parameters is considerably reduced by using an active control strategy. The cameras track a point in space independently of the robot motion and the full rotation of the head, which includes the unknown robot motion, is derived from binocular image data. The feasibility of the approach in real robotic applications is demonstrated by several experiments performed on real image data acquired from an autonomous vehicle and a prototype camera head. >

Transferring and regrasping a large object by cooperation of multiple mobile robots

Abstract: This paper deals with a motion planning of mobile robots during transferring a large object cooperatively by a group of multiple mobile robots (a robot group). This problem has the following characteristics: 1) a real time planning is essential because mobile robots move in an open and dynamic area in comparison to articulated robots; 2) both the object and the robot group need to avoid collision against obstacles; and 3) the object needs to be grasped stably by the robot group. The authors propose the following approach to solve this complicated problem: 1) regrasping strategy of the object is introduced in order avoid obstacles and to transfer the object stably; and 2) the motion planning is divided into two steps: the object and that of the robot group. The former step is accomplished by extending the virtual impedance method, which was proposed by authors. The latter step is realized by using nonlinear programming method, that optimizes a penalty index indicating the performance for obstacle avoidance and for stable grasping. Effectiveness of the proposed method is verified by a simulation of transferring a large circle-shaped object with three robots.

A Bayesian approach to real-time obstacle avoidance for a mobile robot

Abstract: Real-time obstacle avoidance is essential for the safe operation of mobile robots in a dynamically changing environment. This paper investigates how an industrial mobile robot can respond to unexpected static obstacles while following a path planned by a global path planner. The obstacle avoidance problem is formulated using decision theory to determine an optimal response based on inaccurate sensor data. The optimal decision rule minimises the Bayes risk by trading between a sidestep maneuver and backtracking to follow an alternative path. Real-time implementation is emphasised here as part of a framework for real world applications. It has been successfully implemented both in simulation and in reality using a mobile robot.

Coordinated obstacle avoidance of a mobile manipulator

Abstract: In the absence of obstacles, the study of mobile manipulators is mainly concerned with the coordination of locomotion and manipulation. In the presence of obstacles, one must simultaneously consider the obstacle avoidance problem and the coordination problem. This paper presents a control method for mobile manipulators that integrates an obstacle avoidance scheme with a coordination scheme. The obstacle avoidance scheme is based on superquadric potential functions. The coordination scheme is based on preferred operating regions. The controller allows a mobile manipulator to retain optimal or sub-optimal configurations while avoiding obstacles. Simulation results are presented to demonstrate the effectiveness of the control method.

A mobile robot navigation method using a fuzzy logic approach

Abstract: This paper treats, in a general way, the problem of mobile robot navigation in a totally unknown environment. The different aspects of this problem are dealt with one by one. We begin by introducing a simple method for perceiving and analyzing the robot's local environment based on a limited amount of distance information. Using this analysis as our base, we present a navigation algorithm containing different action modules; some of these actions use Fuzzy Logic. The results presented whether experimental or simulation show that our method is well adapted to this type of problem.

A fast approach for the robust trajectory planning of redunant robot manipulators

Abstract: In this article, a fast approach for robust trajectory planning, in the task space, of redundant robot manipulators is presented. The approach is based on combining an original method for obstacle avoidance by the manipulator configuration with the traditional potential field approach for the motion planning of the end-effector. This novel method is based on formulating an inverse kinematics problem under an inexact context. This procedure permits dealing with the avoidance of obstacles with an appropriate and easy to compute null space vector; whereas the avoidance of singularities is attained by the proper pseudoinverse perturbation. Furthermore, it is also shown that this formulation allows one to deal effectively with the local minimum problem frequently associated with the potential field approaches. The computation of the inverse kinematics problem is accomplished by numerically solving a linear system, which includes the vector for obstacle avoidance and a scheme for the proper pseudoinverse perturbation to deal with the singularities and/or the potential function local minima. These properties make the proposed approach suitable for redundant robots operating in real time in a sensor-based environment. The developed algorithm is tested on the simulation of a planar redundant manipulator. From the results obtained it is observed that the proposed approach compares favorably with the other approaches that have recently been proposed. © 1995 John Wiley & Sons, Inc.

Stereo perception and dead reckoning for a prototype lunar rover.

Abstract: This paper describes practical, effective approaches to stereo perception and dead reckoning, and presents results from systems implemented for a prototype lunar rover operating in natural, outdoor environments. The stereo perception hardware includes a binocular head mounted on a motion-averaging mast. This head provides images to a normalized correlation matcher, that intelligently selects what part of the image to process (saving time), and subsamples the images (again saving time) without subsampling disparities (which would reduce accuracy). The implementation has operated successfully during long-duration field exercises, processing streams of thousands of images. The dead reckoning approach employs encoders, inclinometers, a compass, and a turn-rate sensor to maintain the position and orientation of the rover as it traverses. The approach integrates classical odometry with inertial guidance. The implementation succeeds in the face of significant sensor noise by virtue of sensor modelling, plus extensive filtering. The stereo and dead reckoning components are used by an obstacle avoidance planner that projects a finite number of arcs through the terrain map, and evaluates the traversability of each arc to choose a travel direction that is safe and effective. With these components integrated into a complete navigation system, a prototype rover has traversed over 1 km in lunar-like environments.

Robot motion planning among moving obstacles

Abstract: This thesis presents a new approach for planning a robot's trajectory that avoids static and moving obstacles and minimizes motion time, subject to robot dynamics and actuator constraints. This approach consists of first computing a coarse trajectory that avoids the obstacles and satisfies an approximation of the actuator constraints. Then this trajectory is used as the initial guess of a dynamic optimization that satisfies obstacle avoidance, robot dynamics and the true actuator limits. The first step of the approach is based on the concept of Velocity Obstacle (VO) that defines, at every instant in time, the set of colliding velocities between the robot and the obstacles. The VO set is computed using the relative velocity between the robot and each obstacle, and is instrumental in determining the set of robot velocities avoiding all obstacles and satisfying approximate system dynamics and actuator limits. Within this set, the best avoidance maneuver is chosen heuristically so that the trajectory resulting from the sequence of maneuvers reaches the goal and minimizes motion time. The second step of the approach consists of refining the trajectory with a dynamic optimization that minimizes motion time, subject to the true robot's dynamics, actuator constraints, and time varying obstacle constraints. The dynamic optimization is based on Pontryagin's Minimum Principle and uses a gradient descent method. These two steps lead to the implementation of a powerful and flexible planner that combines the advantages of heuristics with those of dynamic optimization. Heuristics in fact, captures the non-analytic aspects of motion planning, such as sequence of obstacle avoidance, conservative or aggressive maneuvers, and so on, thus characterizing the global structure of the trajectory. Dynamic optimization on the other hand, ensures feasibility and optimality of the trajectory thus guaranteeing its local correctness. This approach is demonstrated for planning the motions of an automated vehicle in an Intelligent Vehicle Highway System (IVHS) scenario, and of an articulated robot moving in a dynamic environment. This motion planner is suitable to a wide range of applications. The Velocity Obstacle method is very fast and, although approximate, it can be used for real time planning. The Dynamic Optimization is computationally intensive, but yields optimal solutions, which can be used when off-line planning is acceptable.

An efficient finding of fuzzy rules using a new approach to genetic based machine learning

Abstract: This paper presents a new approach to genetic based machine learning (GBML). The new approach is based on an imaginary mechanism of evolution. The authors call the new approach Nagoya approach. The Nagoya approach is efficient in finding complex rules. An obstacle avoidance of mobile robot is simulated using the new GBML, and complex fuzzy rules are found. >

An obstacle avoidance algorithm for a car pulling trailers with off-axle hitching

Abstract: A new algorithm is presented for planning motion among obstacles for a mobile robot system configured as a car pulling many trailers with off-axle hitching In the special case of equal length hitches, upper bounds on the off-tracking of the trailers and hitches are the key component to the new path planning method, which only needs to plan a collision-free path for an "enlarged" lead car

Time-optimal obstacle avoidance

Abstract: This paper presents a method for generating near-time optimal trajectories in cluttered environments for manipulators with invariant inertia matrices. For one obstacle, the method generates the time-optimal trajectory by minimizing the time-derivative of the return (cost) function for this problem, satisfying the Hamilton-Jacobi-Bellman (HJB) equation. For multiple obstacles, the trajectory is generated using the pseudo return function, which is an approximation of the return function for the multi-obstacle problem. The pseudo return function avoids one obstacle at a time, producing near-optimal trajectories that are guaranteed to avoid the obstacles and satisfy the actuator constraints. An example with circular obstacles demonstrates close correlation between the near-optimal and optimal paths, requiring computational efforts that are suitable for on-line implementations.

Global trajectory planning for fault tolerant manipulators

Abstract: Whether a task can be completed after a failure of one of the degrees-of-freedom of a redundant manipulator depends on the joint angle at which the failure takes place. It is possible to achieve fault tolerance by globally planning a trajectory that avoids unfavorable joint positions before a failure occurs. In this paper we present a trajectory planning algorithm that guarantees fault tolerance while simultaneously satisfying joint limit and obstacle avoidance requirements.

The Kinematics of Hyper-Redundant

Abstract: This paper considers the kinematics of hyper- redundant (or "serpentine") robot locomotion over uneven solid terrain, and presents algorithms to implement a variety of "gaits." The analysis and algorithms are based on a continuous backbone curve model which captures the robot's macroscopic geometry. Two classes of gaits, based on stationary waves and traveling waves of mechanism deformation, are introduced for hyper-redundant robots of both constant and variable length. We also illustrate how the locomotion algorithms can be used to plan the manipulation of objects which are grasped in a tentacle-like manner. Several of these gaits and the manipulation algorithm have been implemented on a 30 degree-of-freedom hyper-redundant robot. Experimental results are presented to demonstrate and validate these concepts and our modeling assumptions. over uneven terrain. These gaits are based on stationary and traveling waves of mechanism deformation, and have analogues in inchworm and caterpillar locomotion and the creeping gaits of snakes. These gaits are largely "kinematic" in nature. That is, dynamic effects and a detailed model of the friction between the mechanism and the ground are not critical to the function or understanding of these gaits at reasonable speeds. In contrast, dynamic effects, the internal distribution of mechanism forces, and a frictional model are important for some gaits, such as those which are analogous to the undulatory and concertina gaits used by snakes. Hence, the analysis in this paper does not cover all possible hyper- redundant robot gaits. The gaits considered in this paper were chosen for their simplicity, implementability, and wide range of applicability. Further, we show how these locomotion algorithms can be used to implement a novel scheme for planning the manipulation of objects which are grasped in a tentacle-like fashion. The gait algorithms are based on a "backbone curve" mod- eling technique that was introduced in earlier works devoted to hyper-redundant manipulator kinematics, trajectory planning, and obstacle avoidance (5), (4), (8). With the backbone curve abstraction, surprisingly simple ideas and mathematics can be used to understand and implement relatively complicated hyper-redundant robot locomotion phenomena. Several of the gaits and the object manipulation scheme have been im- plemented in a 30 degree-of-freedom hyper-redundant robot prototype, and experimental results are also presented to show that the algorithms are indeed able to be implemented.

Trajectory Planning for an Object in Pushing Operation

Abstract: In this paper, we propose a method of trajectory planning for an object in pushing operation, which is to move the object on a floor to desired position and orientation using one arm. The feature of this method is that not only position and orientation of the object but also friction between the arm and the object are considered. We suppose that the distribution of magnitude of friction between the object and the floor is known. First, the state equation of the system and constraint equations about state and control variables are derived from kinematic constraints of the object. Then we make a performance index about distance, and translate the trajectory planning into an optimal control problem with state and input constraints. The trajectory of the object is obtained by solving the problem numerically. In the latter part of this paper, the trajectory planning is extended to that with obstacle avoidance. Numerical examples show the effectiveness of the proposed method.

An analytic approach to moving obstacle avoidance using an artificial potential field

Abstract: This paper proposes a unified method for moving obstacle avoidance of a robot The method incorporates the artificial potential field (APF) concept into view-time based motion planning where the driving force is generated at every interval of the view-time The view-time is defined as the time set from one sampling time instant to the next The velocity and acceleration of the moving obstacle is assumed to be monitored or priorly known at each sampling time At each sampling time, an accessible region that will be swept by the obstacle in the next view-time is predicted from the velocity, acceleration, and dynamic constraints of the obstacle Then, an APF which exerts repulsive force on the robot is constructed around the accessible region During the view-time, the force induced by the artificial potential field drives the robot away from the accessible obstacle trajectories in real-time The dynamic constraints of the robot are also considered Application of the described procedure at each successive sampling time from the initial to final location yields the collision-free trajectory for moving obstacle avoidance