Showing papers on "Motion planning published in 1987"

A simple motion-planning algorithm for general robot manipulators

Abstract: A simple and efficient algorithm is presented, using configuration space, to plan collision-free motions for general manipulators. An implementation of the algorithm for manipulators made up of revolute joints is also presented. The configuration-space obstacles for an n degree-of-freedom manipulator are approximated by sets of n - 1- dimensional slices, recursively built up from one-dimensional slices. This obstacle representation leads to an efficient approximation of the free space outside of the configuration-space obstacles.

New lower bound techniques for robot motion planning problems

Abstract: We present new techniques for establishing lower bounds in robot motion planning problems. Our scheme is based on path encoding and uses homotopy equivalence classes of paths to encode state. We first apply the method to the shortest path problem in 3 dimensions. The problem is to find the shortest path under an Lp metric (e.g. a euclidean metric) between two points amid polyhedral obstacles. Although this problem has been extensively studied, there were no previously known lower bounds. We show that there may be exponentially many shortest path classes in single-source multiple-destination problems, and that the single-source single-destination problem is NP-hard. We use a similar proof technique to show that two dimensional dynamic motion planning with bounded velocity is NP-hard. Finally we extend the technique to compliant motion planning with uncertainty in control. Specifically, we consider a point in 3 dimensions which is commanded to move in a straight line, but whose actual motion may differ from the commanded motion, possibly involving sliding against obstacles. Given that the point initially lies in some start region, the problem of finding a sequence of commanded velocities which is guaranteed to move the point to the goal is shown to be non-deterministic exponential time hard, making it the first provably intractable problem in robotics.

A local based approach for path planning of manipulators with a high number of degrees of freedom

Abstract: This paper presents an alternative to the Potential Field Method of computing local collision-free motions for general manipulators. The main distinction is that we separate the description of the task from constraints of anti-collision. This enables to control accurately all relevant measures of the problem. A task is expressed by the minimization of a function plus eventually some geometric constraints, whereas anti-collision is translated into very simple linear constraints through the methods of the velocity dampers and the tangent separating planes. This approach is applied to the control of manipulators with a high number of degrees of freedom, using hierarchical descriptions of the environment and the robots. This is illustrated by two realizations, path planning for a ten link manipulator in the cluttered environment of a nuclear plant reactor, and cooperative tasks between two six degree of freedom robots. In the end we discuss how to incorporate the action of a global planner in this general framework.

A visual navigation system for autonomous land vehicles

Abstract: A modular system architecture has been developed to support visual navigation by an autonomous land vehicle. The system consists of vision modules performing image processing, three-dimensional shape recovery, and geometric reasoning, as well as modules for planning, navigating, and piloting. The system runs in two distinct modes, bootstrap and feedforward. The bootstrap mode requires analysis of entire images to find and model the objects of interest in the scene (e.g., roads). In the feedforward mode (while the vehicle is moving), attention is focused on small parts of the visual field as determined by prior views of the scene, to continue to track and model the objects of interest. General navigational tasks are decomposed into three categories, all of which contribute to planning a vehicle path. They are called long-, intermediate-, and short-range navigation, reflecting the scale to which they apply. The system has been implemented as a set of concurrent communicating modules and used to drive a camera (carried by a robot arm) over a scale model road network on a terrain board. A large subset of the system has been reimplemented on a VICOM image processor and has driven the DARPA Autonomous Land Vehicle (ALV) at Martin Marietta's test site in Denver, CO.

Uncertain geometry in robotics

Abstract: Robots must operate in an environment which is inherently uncertain. This uncertainty is important in areas such as modeling, planning and the motion of manipulators and objects; areas where geometric analysis also plays an important part. To operate efficiently, a robot system must be able to represent, account for, and reason about the effects of uncertainty in these geometries in a consistent manner. We maintain that uncertainty should be represented as an intrinsic part of all geometric descriptions. We develop a description of uncertain geometric features as families of parameterized functions together with a distribution function defined on the associated parameter vector. We consider uncertain points, curves and surfaces, and show how they can be manipulated and transformed between coordinate frames in an efficient and consistent manner. The effectiveness of these techniques is demonstrated by application to the problem of developing maximal information sensing strategies.

Collision-Free Motion Planning of Two Robots

Abstract: An approach to collision-free motion planning of two moving robots in a common workspace is presented. Each robot is represented by a sphere containing the wrist and the manipulator hand. The results from a strictly straight line trajectory planning method are utilized for planning a path avoiding potential collisions. Due to the distinct nature of the potential collisions between the two moving robots, a new classification of path requirement situations is presented and utilized for planning a collision-free path. Notions of collision map and time scheduling are developed and applied for realizing a collision-free motion planning. A procedure is developed for the time scheduling of the straight line trajectory. An example is shown for the time scheduling of the trajectory, which shows the significance of the proposed approach in collision-free motion planning of the two moving robots.

Handey: A robot system that recognizes, plans, and manipulates

Abstract: We describe a robot system capable of locating a part in an unstructured pile of objects, choose a grasp on the part, plan a motion to reach the part safely, and plan a motion to place the part at a commanded position. The system requires as input a polyhedral world model including models of the part to be manipulated, the robot arm, and any other fixed objects in the environment. In addition, the system builds a depth map, using structured light, of the area where the part is to be found initially. Any other objects present in that area do not have to be modeled.

Task-space tracking with redundant manipulators

Abstract: A controller for redundant manipulators with a small fast manipulator mounted on a positioning part has been developed The controller distributes the fast motion to the small fast manipulator and the slow gross motion to the positioning part A position reference is generated on-line to the positioning part to avoid singularities and the loss of degrees of freedom The task-space position vector is augmented by the generalized coordinates of the positioning part Feedback linearization and decoupling are then applied in the augmented task space to obtain a model consisting of decoupled double integrators These decoupled double integrators are controlled by the use of linear quadratic optimal control In the optimal control problem the performance index is chosen so that the task-space position reference is tracked with a high bandwidth while the reference to the positioning part is tracked with a low bandwidth The controller has been applied to a simple planar redundant manipulator and an eight-link spray painting robot in simulation experiments These simulations showed that a high bandwidth was possible with moderate actuator torques

Using Dynamic Analysis for Realistic Animation of Articulated Bodies

Abstract: A major problem in computer animation is creating motion that appears natural and realistic, particularly in such complex articulated bodies as humans and other animals. At present, truly lifelike motion is produced mainly by copying recorded images, a tedious and lengthy process that requires considerable external equipment. An alternative is the use of dynamic analysis to predict realistic motion. Using dynamic motion control, bodies are treated as masses acting under the influence of external and internal forces and torques. Dynamic control is advantageous because motion is naturally restricted to physically realizable patterns, and many types of motion can be predicted automatically. Use of dynamics is computationally expensive and specifying controlling forces and torques can be difficult. However, there is evidence that dynamics offers hope for more realistic, natural, and automatic motion control. Because such motion simulates real world conditions, an animation system using dynamic analysis is also a useful tool in such related fields as robotics and biomechanics.

Formulation of Joint Trajectories for Industrial Robots Using B-Splines

Abstract: In this paper, we describe a new procedure for constructing robot trajectories. The procedure uses the theory of B-splines. The motion of the robot, as specified by a time sequence of position and orientation knots of the end effector, is first transformed into sets of joint displacements. B-splines are then used to fit these sequences for each joint. The procedure consists of a simple recursive algorithm and allows constraints to be imposed on the magnitudes of the joint velocities and accelerations as well as on their initial and final values. A trajectory constructed by this method has the property that a local modification can be made quickly and easily without recomputing the entire trajectory. The method has been used for generating trajectories for a PUMA 560 robot.

Toward Automatic Motion Control

Abstract: Motion control for computer animation is a rich area for new research. The trend toward greater complexity in animation makes the development of more convenient and automatic methods of motion control important. Most commonly used motion control methods, such as keyframing and scripts, require a great deal of user effort to design acceptable animations. More automic methods will allow the production of sophisticated animation with less user effort. These methods include dynamic analysis, path planning and collision avoidance, stimulus-response control, and learning algorithms.

Modeling impact dynamics for robotic operations

Abstract: The motion of an object to be manipulated is determined by the forces applied to the object. During a collision, impulsive forces may dominate all other forces, and determine the ultimate success or failure of a task. More effective planning and control of manipulators should be possible if the impact process, including the effects of friction and elasticity, is better understood. This paper explores the planar impact of two objects, and develops simple graphical methods for predicting the mode of contact, the total impulse, and the resultant motions of the objects. In the special case of a perfectly plastic collision, the fundamental motion of the object-whether an angular acceleration will occur, and if so in what direction-is the same as predicted in earlier work on quasi-static pushing.

Sensor integration for robot navigation: Combining sonar and stereo range data in a grid-based representataion

Abstract: Multiple range sensors are essential in mobile robot navigation systems. This introduces the problem of integrating noisy range data from multiple sensors and multiple robot positions into a common description of the environment. We propose a cellular representation called the occupancy grid as a solution to this problem. In this paper, we use occupancy grids to combine range information from sonar and one-dimensional stereo into a two-dimensional map of the vicinity of a robot. Each cell in the map contains a probabilistic estimate of whether it is empty or occupied by an object in the environment. These estimates are obtained from sensor models that describe the uncertainty in the range data. A Bayesian estimation scheme is used to update the existing map with successive range profiles from each sensor. This representation is simple to manipulate, treats different sensors uniformly, and models uncertainty in the sensor data and in the robot position. It also provides a basis for motion planning and creation of higherlevel object descriptions.

Effect of kinematics on motion planning for planar robot arms moving amidst unknown obstacles

Abstract: An approach of dynamic path planning (DPP) was introduced elsewhere, and nonheuristic algorithms were described for planning collision-free paths for a point automaton moving in an environment filled with unknown obstacles of arbitrary shape. The DPP approach was further extended to a planar robot arm with revolute joints; in this case, every point of the robot body is subject to collision. Under the accepted model, the robot, using information about its immediate surroundings provided by the sensory feedback, continuously (dynamically) generates its path. Various kinematic configurations of planar arms with revolute and sliding joints are analyzed in this paper from the standpoint of applying the same strategy. It is shown that, depending on the arm kinematics, specific modifications must be introduced in the path planning algorithm to preserve convergence. The approach presents an attractive method for robot motion planning in unstructured environments with uncertainty.

A constraint oriented approach to inverse problems for kinematically redundant manipulators

Abstract: Recently a number of measures of mechanism dexterity have been proposed in the robotics literature. These are defined as functions of the configuration, and are primarily promoted as criteria which should be optimized in the planning of robot motions. In this paper, a coordinate-free version of the manipulatability index is presented. This permits the index to be evaluated in a meaningful way for a (kinematically redundant) mechanism operating under imposed functional constraints on the joint variables. Such an intrinsic quantity is useful for deciding which of several possible constraints yields the best performance of a given mechanism, and conversely, it may be employed as a constraint oriented figure-of-merit in the design of kinematically redundant manipulators. It also provides a new computational tool for finding the singularitites inherent in most approaches to redundancy resolution by means of functional constraints.

Robot path planning using intersecting convex shapes: Analysis and simulation

Abstract: An automated path planning algorithm for a mobile robot in a structured environment is presented. An algorithm based on the Quine-McCluskey method of finding prime implicants in a logical expression is used to isolate all the largest rectangular free convex areas in a specified environment. The free convex areas are represented as nodes in a graph, and a graph traversal strategy that dynamically allocates costs to graph paths is used. Complexity of the algorithm and a strategy to trade optimality for smaller computation time are discussed.

Planning and Teaching Compliant Motion Strategies

Abstract: : This thesis presents a new high level robot programming system. The programming system is used to construct strategies consisting of compliant motions, in which a moving robot slides along obstacles in its environment. The programming system is high level because the user is spared of many robot-level details, such as the specification of conditional tests, motion termination conditions, and compliance parameters. The user specifies task-level information, including a geometric model of the robot and its environment. The user may have to specify some suggested motions. There are two mains system components. The first is an interactive teaching system which accepts motion commands from a user and attempts to build a compliant motion strategy using the specified motions as building blocks. The second is an autonomous compliant motion planner, which is intended to spare the user from dealing with simple problems. The planner simplifies the representation of the environment by decomposing the configuration space of the robot into a finite state space, whose states are vertices, edges, faces, and combinations thereof. States are linked to each other by arcs, which represent reliable compliant motions. Using best first search, states are expanded until a strategy is found from the start state to a goal state. This component represents one of the first implemented compliant motion planners. The programming system has been implemented on a Symbolics 3600 computer, and tested on several examples. One of the resulting complaint motion strategies was successfully executed on an IBM 7565 robot manipulator.

Structuring Free Space as a Hypergraph for Roving Robot Path Planning and Navigation

Abstract: This paper presents a method of structuring the free space of a roving robot's environment into a set of overlapping convex regions ideally suited to path planning and navigation tasks. The structure of the free space environment is maintained as a hypergraph with each convex region represented by a hyperedge identifying the boundary walls of the region. A new methodology reveals the structure of free space and constructs the hypergraph representation through a directed search for a set of fundamental circits in an abstract graphical representation of the environment geometry.

Certainty grids for mobile robots

Abstract: A numerical representation of uncertain and incomplete sensor knowledge called Certainty Grids has been used successfully in several mobile robot control programs, and has proven itself to be a powerful and efficient unifying solution for sensor fusion, motion planning, landmark identification, and many other central problems. Researchers propose to build a software framework running on processors onboard the new Uranus mobile robot that will maintain a probabilistic, geometric map of the robot's surroundings as it moves. The certainty grid representation will allow this map to be incrementally updated in a uniform way from various sources including sonar, stereo vision, proximity and contact sensors. The approach can correctly model the fuzziness of each reading, while at the same time combining multiple measurements to produce sharper map features, and it can deal correctly with uncertainties in the robot's motion. The map will be used by planning programs to choose clear paths, identify locations (by correlating maps), identify well-known and insufficiently sensed terrain, and perhaps identify objects by shape. The certainty grid representation can be extended in the same dimension and used to detect and track moving objects.

A new efficient motion-planning algorithm for a rod in two-dimensional polygonal space

Abstract: We present here a new and efficient algorithm for planning collision-free motion of a line segment (a rod or a “ladder”) in two-dimensional space amidst polygonal obstacles. The algorithm uses a different approach than those used in previous motion-planning techniques, namely, it calculates the boundary of the (three-dimensional) space of free positions of the ladder, and then uses this boundary for determining the existence of required motions, and plans such motions whenever possible. The algorithm runs in timeO(K logn) =O(n 2 logn) wheren is the number of obstacle corners and whereK is the total number of pairs of obstacle walls or corners of distance less than or equal to the length of the ladder. The algorithm has thus the same complexity as the best previously known algorithm of Leven and Sharir [5], but if the obstacles are not too cluttered together it will run much more efficiently. The algorithm also serves as an initial demonstration of the viability of the technique it uses, which we expect to be useful in obtaining efficient motion-planning algorithms for other more complex robot systems.

Vision guided robotic fabric manipulation for apparel manufacturing

Abstract: This paper details methods pertaining to the vision guided robotic control of fabric motion for performing simulated joining operations along the fabric edge. Robot motion paths are determined from visual information defining the position of the fabric edges. The function of the shape analysis and motion control algorithms is demonstrated via experimentation with an automated fabric handling system, Results of these tests show that using machine vision for planning robot motion provides an effective solution for implementing robotic fabric manipulation.

A decentralized approach to the motion planning problem for multiple mobile robots

Abstract: In this paper the motion planning problem for multiple mobile robots is addressed. Conventional methods of planning the motion for a single moving object are based on the assumption of a static environment, and so they cannot be used here because each of the robots is in a dynamic environment consisting of other moving robots. Centralized approaches to the multiple moving objects problem were shown to be intractable. In order to find a practical solution for the problem, it is necessary to reduce the complexity of it by decomposing the problem and introducing various heuristic techniques. We are proposing here a decentralized approach which is based on the decomposition of the problem into two subproblems: the global path planning problem and the local path replanning problem. This approach is based on a framework of problem solving using a group of intelligent agents.

Qualitatne landmark-based path planning and following

Abstract: This paper develops a theory for path planning and following using visual landmark recognition for the representation of environmental locations. It encodes local perceptual knowledge in structures called viewframes and orientation regions. Rigorous representations of places as visual events are developed in a uniform framework that smoothly integrates a qualitative version of path planning with inference over traditional metric representations. Paths in the world are represented as sequences of sets of landmarks, viewframes. orientation boundary crossings, and other distinctive visual events. Approximate headings are computed between view frames that have lines of sight to common landmarks. Orientation regions are range-free, topological descriptions of place that are rigorously abstracted from viewframes. They yield a coordinate-free model of visual landmark memory that can also be used for path planning and following. With this approach, a robot can opportunistically observe and execute visually cued "shortcuts".

A singularities avoidance method for the trajectory planning of redundant and nonredundant robot manipulators

Abstract: In this paper, a singularities avoidance method suitable for the trajectory planning of redundant and nonredundant robot manipulators is presented. This method is based on establishing proper bounds for the rate of change of the Jacobian matrix of the transformation between the joints speed and end effector Cartesian speed These bounds are computationally inexpensive and easy to deal with by their conversion into additional constraints for any optimization problem which may be formulated to obtain the local or global optimal control of the robot manipulator. Here, this approach is exemplified for the trajectory planning problem of a particular type of redundant and nonredundant robot manipulators studied under an optimal control problem formulation. For each case, this problem is treated as a minimum energy problem with given kinematics and dynamics and subject to the robot requirements, tasks, and the additional singularities avoidance constraints; resulting in a state constrained continuous optimal control which is solved numerically.