Showing papers on "Robot published in 1992"

Exact robot navigation using artificial potential functions

Abstract: A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented. Complete information about a freespace and goal is encoded in the form of a special artificial potential function, called a navigation function, that connects the kinematic planning problem with the dynamic execution problem in a provably correct fashion. The navigation function automatically gives rise to a bounded-torque feedback controller for the robot's actuators that guarantees collision-free motion and convergence to the destination from almost all initial free configurations. A formula for navigation functions that guide a point-mass robot in a generalized sphere world is developed. The simplest member of this family is a space obtained by puncturing a disk by an arbitrary number of smaller disjoint disks representing obstacles. The other spaces are obtained from this model by a suitable coordinate transformation. Simulation results for planar scenarios are provided. >

A new approach to visual servoing in robotics

Abstract: Vision-based control in robotics based on considering a vision system as a specific sensor dedicated to a task and included in a control servo loop is described. Once the necessary modeling stage is performed, the framework becomes one of automatic control, and stability and robustness questions arise. State-of-the-art visual servoing is reviewed, and the basic concepts for modeling the concerned interactions are given. The interaction screw is thus defined in a general way, and the application to images follows. Starting from the concept of task function, the general framework of the control is described, and stability results are recalled. The concept of the hybrid task is presented and then applied to visual sensors. Simulation and experimental results are presented, and guidelines for future work are drawn in the conclusion. >

Numerical potential field techniques for robot path planning

Abstract: An approach to robot path planning that consists of incrementally building a graph connecting the local minima of a potential field defined in the robot's configuration space and concurrently searching this graph until a goal configuration is attained is proposed. Unlike the so-called global path planning methods, this approach does not require an expensive computation step before the search for a path can actually start, and it searches a graph that is usually much smaller than the graph searched by the so-called local methods. A collection of effective techniques to implement this approach is described. They are based on the use of multiscale pyramids of bitmap arrays for representing both the robot's workspace and configuration space. This distributed representation makes it possible to construct potential fields numerically, rather than analytically. A path planner based on these techniques has been implemented. Experiments with this planner show that it is both very fast and capable of handling many degrees of freedom. >

Gross motion planning—a survey

Abstract: Motion planning is one of the most important areas of robotics research. The complexity of the motion-planning problem has hindered the development of practical algorithms. This paper surveys the work on gross-motion planning, including motion planners for point robots, rigid robots, and manipulators in stationary, time-varying, constrained, and movable-object environments. The general issues in motion planning are explained. Recent approaches and their performances are briefly described, and possible future research directions are discussed.

Integration of representation into goal-driven behavior-based robots

Abstract: An architecture that integrates a map representation into a reactive, subsumption-based mobile robot is described. This fully integrated reactive system removes the distinction between the control program and the map. The method was implemented and tested on a mobile robot equipped with a ring of sonars and a compass, and programmed with a collection of simple, incrementally designed behaviors. The robot performs collision-free navigation, dynamic landmark detection, map construction and maintenance, and path planning. Given any known landmark as a goal, the robot plans and executes the shortest known path to it. If the goal is not reachable, the robot detects failure, updates the map, and finds an alternate route. The topological representation primitives are designed to suit the robot's sensors and its navigation behavior, thus minimizing the amount of stored information. Distributed over a collection of behaviors, the map itself performs constant-time localization and linear-time path planning. The approach is qualitative and robust. >

Command Control for Many-Robot Systems

Abstract: Rapidly evolving sensor, effector and processing technologies, including micromechanical fabrication techniques, will soon make possible the development of very inexpensive autonomous mobile devices with adequate processing but fairly limited sensor capabilities. One goal which has been proposed is to employ large numbers (more than 100) of these simple robots to achieve real-world military mission goals in the ground, air, and underwater environments, using sensor-based reactive planners to realize desired emergent collective group behaviors. One key prerequisite to realizing this goal is the capability to command and control the system of robots in terms of meaningful mission-oriented system-level parameters. A commander requires an understanding of a system's capabilities, doctrine for employing it, and measures of effectiveness to assess its performance once deployed. It is thus necessary to relate system (ensemble) functionality and performance to the behaviors realized by the individual autonomous elements. This paper describes a program of analysis, modeling, algorithm development, and simulation which has been undertaken to develop, refine, and validate this basic approach to real-world problem solving. The initial thrust has been to develop generic behaviors, such as blanket, barrier, and sweep coverage, and various deployment and recovery modes, which can address a broad spectrum of generic applications such as mine deployment, minesweeping, surveillance, sentry duty, maintenance inspection, ship hull cleaning, and communications relaying. Initial simulation results are presented. 1.0 INTRODUCTION The critical sensor, effector, and processing technologies that are prerequisite to the development of the military mobile robots of the 21st century are evolving rapidly. Moreover, while major thrusts in the development of military mobile robots have been undertaken in the areas of Unmanned Ground Vehicles (UGVs), Unmanned Air Vehicles (UAVs), and Unmanned Underwater Vehicles (UUVs), continuing developments in solid-state sensor and effector technologies suggest that unexploited opportunities exist at the "lower end" of the spectrum of robotic vehicle functionality and performance [1, 2]. In fact, the emerging field of "micromachines" (also termed "microdynamics", "mechatronics", or "microelectromechanical systems") was selected

Dynamic map building for an autonomous mobile robot

Abstract: This article presents an algorithm for autonomous map building and maintenance for a mobile robot. We believe that mobile robot navigation can be treated as a problem of tracking ge ometric features that occur naturally in the environment. We represent each feature in the map by a location estimate (the feature state vector) and two distinct measures of uncertainty: a covariance matrix to represent uncertainty in feature loca tion, and a credibility measure to represent our belief in the validity of the feature. During each position update cycle, pre dicted measurements are generated for each geometric feature in the map and compared with actual sensor observations. Suc cessful matches cause a feature's credibility to be increased. Unpredicted observations are used to initialize new geometric features, while unobserved predictions result in a geometric feature's credibility being decreased. We describe experimental results obtained with the algorithm that demonstrate successful map building using real son...

Integrating planning and reacting in a heterogeneous asynchronous architecture for controlling real-world mobile robots

Abstract: This paper presents a heterogeneous, asynchronous architecture for controlling autonomous mobile robots which is capable of controlling a robot performing multiple tasks in real time in noisy, unpredictable environments. The architecture produces behavior which is reliable, task-directed (and taskable), and reactive to contingencies. Experiments on real and simulated realworld robots are described. The architecture smoothly integrates planning and reacting by performing these two functions asynchronously using heterogeneous architectural elements, and using the results of planning to guide the robot's actions but not to control them directly. The architecture can thus be viewed as a concrete implementation of Agre and Chapman's plans-ascommunications theory. The central result of this work is to show that completely unmodified classical AI programming methodologies using centralized world models can be usefully incorporated into real-world embedded reactive systems.

A passivity approach to controller-observer design for robots

Abstract: Passivity-based control methods for robots, which achieve the control objective by reshaping the robot system's natural energy via state feedback, have, from a practical point of view, some very attractive properties. However, the poor quality of velocity measurements may significantly deteriorate the control performance of these methods. In this paper the authors propose a design strategy that utilizes the passivity concept in order to develop combined controller-observer systems for robot motion control using position measurements only. To this end, first a desired energy function for the closed-loop system is introduced, and next the controller-observer combination is constructed such that the closed-loop system matches this energy function, whereas damping is included in the controller- observer system to assure asymptotic stability of the closed-loop system. A key point in this design strategy is a fine tuning of the controller and observer structure to each other, which provides solutions to the output-feedback robot control problem that are conceptually simple and easily implementable in industrial robot applications. Experimental tests on a two-DOF manipulator system illustrate that the proposed controller-observer systems enable the achievement of higher performance levels compared to the frequently used practice of numerical position differentiation for obtaining a velocity estimate. >

Artificial Life and Real Robots

Abstract: The first part of this paper explores the general issues in using Artificial Life techniques to program actual mobile robots. In particular it explores the difficulties inherent in transferring programs evolved in a simulated environment to run on an actual robot. It examines the dual evolution of organism morphology and nervous systems in biology. It proposes techniques to capture some of the search space pruning that dual evolution offers in the domain of robot programming. It explores the relationship between robot morphology and program structure, and techniques for capturing regularities across this mapping. The second part of the paper is much more specific. It proposes techniques which could allow realistic explorations concerning the evolution of programs to control physically embodied mobile robots. In particular we introduce a new abstraction for behavior-based robot programming which is specially tailored to be used with genetic programming techniques. To compete with hand coding techniques it will be necessary to automatically evolve programs that are one to two orders of magnitude more complex than those previously reported in any domain. Considerable extensions to previously reported approaches to genetic programming are necessary in order to achieve this goal.

SSS: a hybrid architecture applied to robot navigation

Abstract: Describes a three-layer architecture, SSS, for robot control. It combines a servo-control layer, a subsumption layer, and a symbolic layer in a way that allows the advantages of each technique to be fully exploited. The key to this synergy is the interface between the individual subsystems. The design of situation recognizers that bridge the gap between the servo and subsumption layers, and event detectors that link the subsumption layers and symbolic layers are discussed. The development of such a combined system is illustrated by a fully implemented indoor navigation example. The resulting robot was able to automatically map office building environments, and smoothly navigate through them at the rapid speed of 2.6 feet per second. >

Sequencing of Parts and Robot Moves in a Robotic Cell

Abstract: In this paper, we deal with the problem of sequencing parts and robot moves in a robotic cell where the robot is used to feed machines in the cell. The robotic cell, which produces a set of parts of the same or different types, is a flow-line manufacturing system. Our objective is to maximize the long-run average throughput of the system subject to the constraint that the parts are to be produced in proportion of their demand. The cycle time formulas are developed and analyzed for this purpose for cells producing a single part type using two or three machines. A state space approach is used to address the problem. Both necessary and sufficient conditions are obtained for various cycles to be optimal. Finally, in the case of many part types, the problem of scheduling parts for a specific sequence of robot moves in a two machine cell is formulated as a solvable case of the traveling salesman problem.

A mobile robot exploration algorithm

Abstract: An algorithm for path planning to a goal with a mobile robot in an unknown environment is presented. The robot maps the environment only to the extent necessary to achieve the goal. Mapping is achieved using tactile sensing while the robot is executing a path to the specified goal. Paths are generated by treating unknown regions in the environment as free space. As obstacles are encountered en route to a goal, the model of the environment is updated and a new path to the goal is planned and executed. Initially the paths to the goal generated by this algorithm will be negotiable paths. However, as the robot acquires more knowledge about the environment, the length of the planned paths will be optimized. The optimization criteria can be modified to favor or avoid unexplored regions in the environment. The algorithm makes use of the quadtree data structure to model the environment and uses the distance transform methodology to generate paths for the robot to execute. >

Minimizing complexity in controlling a mobile robot population

Abstract: The author addresses the problem of distributing a task over a collection of homogeneous mobile robots. In contrast to hierarchical methods, which assign a leadership hierarchy and a priori roles to different robots, the proposed approach attempts to detect and utilize the run-time group dynamics within the robot collective. The authors apply a distributed control approach both on the level of the individual robot and on the level of the colony. This choice involves a number of tradeoffs. The complexity of a traditional centralized planner is replaced by the complexity of inter-robot and inter-behavior dynamics. The authors explore methods for not only overcoming interference but utilizing those dynamics to achieve super-linear improvements in task performance. They report the results of testing this architecture on a collection of homogeneous mobile robots. The robots were tested on a number of tasks with a series of more intelligent and efficient local control strategies. >

Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties

Abstract: The model-based vision system described in this paper allows a mobile robot to navigate indoors at an average speed of 8 to 10 m/min using ordinary laboratory computing hardware of approximately 16 MIPS power. The navigation capabilities of the robot are not impaired by the presence of stationary or moving obstacles. The vision system maintains a model of uncertainty and keeps track of the growth of uncertainty as the robot travels toward the goal position. The estimates of uncertainty are then used to predict bounds on the locations and orientations of landmarks expected to be seen in a monocular image. This greatly reduces the search for establishing correspondence between the features visible in the image and the landmarks. Given a sequence of image features and a sequence of landmarks derived from a geometric model of the environment, a special aspect of our vision system is the sequential reduction in the uncertainty as each image feature is matched successfully with a landmark, allowing subsequent features to be matched more easily; this is a natural by-product of the manner in which we use Kalman filter-based updating.

Genetic programming approach to the construction of a neural network for control of a walking robot

Abstract: The authors describe the staged evolution of a complex motor pattern generator (MPG) for the control of a walking robot. The experiments were carried out on a six-legged, Brooks-style insect robot. The MPG was composed of a network of neurons with weights determined by genetic algorithm optimization. Staged evolution was used to improve the convergence rate of the algorithm. First, an oscillator for the individual leg movements was evolved. Then, a network of these oscillators was evolved to coordinate the movements of the different legs. By introducing a staged set of manageable challenges, the algorithm's performance was improved. >

Fast Vision-guided Mobile Robot Navigation Using Model-based Reasoning And Prediction Of Uncertainties

Abstract: The model-based vision system described in this thesis allows a mobile robot to navigate indoors at an average speed of 8 meters/minute using ordinary laboratory computing hardware of approximately 16 MIPS power. The navigation capabilities of the robot are not impaired by the presence of the stationary or moving obstacles. The vision system maintains a model of uncertainty and keeps track of the growth of uncertainty as the robot travels towards the goal position. The estimates of uncertainty are then used to predict bounds on the locations and orientations of landmarks expected to be seen in a monocular image. This greatly reduces the search for establishing correspondence between the features visible in the image and the landmarks. Given a sequence of image features and a sequence of landmarks derived from a geometric model of the environment, a special aspect of our vision system is the sequential reduction in the uncertainty as each image feature is matched successfully with a landmark, allowing subsequent features to be matched more easily, this being a natural byproduct of the manner in which we use Kalman-filter based updating. Strategies for path planning, path replanning and perception planning are introduced for the robot to navigate in the presence of obstacles. Finally, experimental results are presented.

Force sensing and control for a surgical robot

Abstract: The authors describe the use of force feedback in a surgical robot system (ROBODOC). The application initially being addressed is total hip replacement (THR) surgery, where the robot must prepare a cavity in the femur for an artificial implant. In this system, force feedback is used to provide safety, tactile search capabilities, and an improved man-machine interface. Output of the force sensor is monitored by a safety processor, which initiates corrective action if any of several application-defined thresholds are exceeded. The robot is able to locate objects using guarded moves and force control (ball-in-cone strategy). In addition, the force control algorithm provides an intuitive man-machine interface which allows the surgeon to guide the robot by leading its tool to the desired location. An application of force control currently under development is described, where the force feedback is used to modify the cutter feed rate (force controlled velocity). >

On geometric assembly planning

Abstract: This dissertation addresses the problem of generating feasible assembly sequences for a mechanical product from a geometric model of the product. An operation specifies a motion to bring two subassemblies together to make a larger subassembly. An assembly sequence is a sequence of operations that construct the product from the individual parts. I introduce the non-directional blocking graph, a succinct characterization of the blocking relationships between parts in an assembly. I describe efficient algorithms to identify removable subassemblies by constructing and analyzing the NDBG. For an assembly A of n parts and m part-part contacts equivalent to k contact points, a subassembly that can translate a small distance from the rest of A can be identified in $O(mk\sp2)$ time. When rotations are allowed as well, the time bound is $O(mk\sp5)$. Both algorithms are extended to find connected subassemblies in the same time bounds. All free subassemblies can be identified in output-dependent polynomial time. Another algorithm based on the NDBG identifies subassemblies that can be completely removed by a single translation. For a polyhedral assembly with v vertices, the algorithm finds a removable subassembly and direction in $O(n\sp2v\sp4)$ time. When applied to find the set of translations separating two parts, the algorithm is optimal. A final method accelerates the generation of linear assembly sequences, in which each operation mates a single part with a subassembly. The results of geometric calculations are stored in logical expressions and later retrieved to answer similar geometric queries. Several types of expressions with increasing descriptive power are given. An assembly sequencing testbed called GRASP was implemented using the above methods. From standard three-dimensional model of a product, GRASP finds part contacts and motion constraints, and constructs an AND/OR graph representing a set of geometrically feasible assembly sequences for the product. Experimental results are shown for several complex products.

Path planning for a mobile robot

Abstract: Two problems for path planning of a mobile robot are considered. The first problem is to find a shortest-time, collision-free path for the robot in the presence of stationary obstacles in two dimensions. The second problem is to determine a collision-free path (greedy in time) for a mobile robot in an environment of moving obstacles. The environment is modeled in space-time and the collision-free path is found by a variation of the A* algorithm. >

Dynamic feedback linearization of nonholonomic wheeled mobile robots

Abstract: Smooth time-varying laws can solve the stabilization problem of nonholonomic mechanical systems. The authors show that by means of dynamic state feedback, it is possible for three-wheeled mobile robots to track arbitrary fast trajectories not reduced to equilibrium points. Dynamical modeling of nonholonomic mechanical systems for the case of three-wheeled mobile robots is considered. Dynamic feedback allows solution of the tracking problem for an omnidirectional mobile robot with less motors than degrees of freedom. This is possible by choosing output functions depending on the mass repartition of the robot. >

Contact stability for two-fingered grasps

Abstract: Two types of grasp stability, spatial grasp stability and contact grasp stability, each with a different concept of the state of a grasp, are distinguished and characterized. Examples are presented to show that spatial stability cannot capture certain intuitive concepts of grasp stability and hence that any full understanding of grasp stability must include contact stability. A model of how the positions of the points of contact evolve in time on the surface of a grasped object in the absence of any external force or active feedback is then derived. From the model, a general measure of the contact stability of any two-fingered grasp is obtained. Finally, the consequences of this stability measure and a related measure of contact manipulability on strategies for grasp selection are discussed. >

Teleprogramming: Toward delay-invariant remote manipulation

Abstract: This paper addresses the problem of teleoperation in the presence of communication delays. Delays occur with earth-based teleoperation in space and with surface-based teleoperation undersea using untethered submersibles and acoustic communication links. The delay in obtaining position and force feedback from the remote slave arms makes direct teleoperation infeasible. We are proposing a control methodology, called teleprogramming, which draws on the experience in the development of supervisory control techniques and robotics over the last three decades and introduces a number of new ideas in operator-model interaction as well as the nature and content of the information being sent to the slave robot. A teleprogramming system allows the operator to kinesthetically, as well as visually, interact with a graphic simulation of the remote environment and to interactively, online teleprogram the remote manipulator through a sequence of elementary robot instructions. A key feature and contribution of this work is the fact that these instructions are generated automatically, in real time, based on the operator's interaction with the simulated environment. The slave robot executes these commands delayed in time and, should an error occur, allows the operator to specify the necessary corrective actions and continue with the task. We will in this paper introduce the overall teleprogramming control concept, describe its main components, and report on the preliminary results using our experimental teleprogramming system.

Explanation-Based Neural Network Learning for Robot Control

Abstract: How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data sets. We introduce a neural network learning method that generalizes rationally from many fewer data points, relying instead on prior knowledge encoded in previously learned neural networks. For example, in robot control learning tasks reported here, previously learned networks that model the effects of robot actions are used to guide subsequent learning of robot control functions. For each observed training example of the target function (e.g. the robot control policy), the learner explains the observed example in terms of its prior knowledge, then analyzes this explanation to infer additional information about the shape, or slope, of the target function. This shape knowledge is used to bias generalization when learning the target function. Results are presented applying this approach to a simulated robot task based on reinforcement learning.

The NIST SPIDER, A Robot Crane.

Abstract: The Robot Systems Division of the National Institute of Standards and Technology has been experimenting for several years with new concepts for robot cranes. These concepts utilize the basic idea of the Stewart Platform parallel link manipulator. The unique feature of the NIST approach is to use cables as the parallel links and to use winches as the actuators. So long as the cables are all in tension, the load is kinematically constrained, and the cables resist perturbing forces and moments with equal stiffness to both positive and negative loads. The result is that the suspended load is constrained with a mechanical stiffness determined by the elasticity of the cables, the suspended weight, and the geometry of the mechanism. Based on these concepts, a revolutionary new type of robot crane, the NIST SPIDER (Stewart Platform Instrumented Drive Environmental Robot) has been developed that can control the position, velocity, and force of tools and heavy machinery in all six degrees of freedom (x, y, z, roll, pitch, and yaw). Depending on what is suspended from its work platform, the SPIDER can perform a variety of tasks. Examples are: cutting, excavating and grading, shaping and finishing, lifting and positioning. A 6 m version of the SPIDER has been built and critical performance characteristics analyzed.

Kinematics, dynamics and control of wheeled mobile robots

Abstract: The controllability of nonholonomic robot systems is proved for six common wheel and axle configurations that possess two or three degrees of freedom. After the kinematics and dynamics were modeled using the synchro-drive vehicle as an example, it was proved that continuous feedback stabilization of the vehicle to an equilibrium point is impossible. The dynamic model so developed is also used to prove that simple controllers are sufficient to guarantee stability for the drive- and steering-angle components of synchro-drive vehicles. Although the underlying control systems are stable, the experimental results demonstrated that potential-field navigation can lead robot trajectories to an unexpected invariant set. The results reported can easily be extended to the modeling and control of other mobile robot systems. >

Landmark-based robot navigation

Abstract: To operate in the real world robots must deal with errors in control and sensing. Achieving goals despite these errors requires complex motion planning and plan monitoring. We present a reduced version of the general problem and a complete planner that solves it in polynomial time. The basic concept underlying this planner is that of a landmark. Within the field of influence of a landmark, robot control and sensing are perfect. Outside any such field control is imperfect and sensing is null. In order to make sure that the above assumptions hold, we may have to specifically engineer the robot workspace. Thus, for the first time, workspace engineering is seen as a means to make planning problems tractable. The planner was implemented and experimental results are presented. An interesting feature of the planner is that it always returns a universal plan in the form of a collection of reaction rules. This plan can be used even when the input problem has no guaranteed solution, or when unexpected events oceur during plan execution.

Robot with virtual arm positioning based on sensed camera image

Abstract: A robot numerical control apparatus for following a program and utilizing, in the program, the result of processing an image obtained by a camera attached to an arm of a robot. Either a first command for displacing the manipulating end of the robot to a designated position or a second command for displacing the center of the output image of the camera to the designated position is selectable as a displacement command to actuate the robot. A coordinate transformer is provided for controlling the movement of the robot's arm with pseudo-control in such a manner that when the second command is selected the center of the sensed image is positioned at the manipulating end of a virtual arm measured from the center of the sensed image to the center of the articulation of the robot's arm equipped with the camera, whereby the subject being photographed can be caught exactly at the image sensing center of the camera attached to the robot's arm.

SANDROS: a motion planner with performance proportional to task difficulty

Abstract: To address the need of a practical motion planner for manipulators, the authors present an efficient and resolution-complete algorithm that has performance commensurate with task difficulty. The algorithm uses SANDROS, a search strategy that combines hierarchical, nonuniform multiresolution, and best-first search to find a near-optimal solution in the configuration space. This algorithm can be applied to any manipulator, and has been tested with five- and six-degree-of-freedom robots, with execution times ranging from 20 seconds to 10 minutes on a 16 MIPS workstation. >