Showing papers on "Robot published in 1997"

The dynamic window approach to collision avoidance

Abstract: This approach, designed for mobile robots equipped with synchro-drives, is derived directly from the motion dynamics of the robot. In experiments, the dynamic window approach safely controlled the mobile robot RHINO at speeds of up to 95 cm/sec, in populated and dynamic environments.

High Precision Formation Control of Mobile Robots Using Virtual Structures

Abstract: A key problem in cooperative robotics is the maintenance of a geometric configuration during movement. To address this problem, the concept of a Virtual Structure is introduced. Using this idea, a general control strategy is developed to force an ensemble of robots to behave as if they were particles embedded in a rigid structure. The method was instantiated and tested using both simulation and experimentation with a set of 3 differential drive mobile robots. Results are presented that demonstrate that this approach is capable of achieving high precision movement that is fault tolerant and exhibits graceful degradation of performance. In addition, this algorithm does not require leader selection as in other cooperative robotic strategies. Finally, the method is inherently highly flexible in the kinds of geometric formations that can be maintained.

RoboCup: The Robot World Cup Initiative

Abstract: The Robot World Cup Initiative (R, oboCup) is attempt to foster AI and intelligent rohoties research by providing a standard problem where wide range of technologies especially concerning multi-agent research (:an be integrated and examined. The first RoboCup competition is to be, heht at. IJCAI-97, Nagoya. In order for a robot team to actually perform a soccer game. various technologies must I)e incorl)orated including: design principles of autononmus agents, multi-agent collaboration, strategy acquisition, real-time rea.~oning, robotics, and sensor-fllsion. Unlike AAAI robot competition, which is tuned for a single heavy-duty slow-moving robot. RoboCup is a task for a team of multiple f‘ast-moving robots under a dynamic environmen(. Although RoboCnp’s final target is a worhl cup with real robots, RoboCup offers a soft.ware platform for reseaxch on the software aspects of RoboCup. This paper describes teclini(’M challenges involw~d in RoboCup, rules, and simulation environment.

Mobile robot localization using landmarks

Abstract: We describe an efficient method for localizing a mobile robot in an environment with landmarks. We assume that the robot can identify these landmarks and measure their bearings relative to each other. Given such noisy input, the algorithm estimates the robot's position and orientation with respect to the map of the environment. The algorithm makes efficient use of our representation of the landmarks by complex numbers. The algorithm runs in time linear in the number of landmarks. We present results of simulations and propose how to use our method for robot navigation.

Mobile Robot Positioning - Sensors and Techniques

Abstract: : Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In the search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: (1) Odometry, (2) Inertial Navigation, (3) Magnetic Compasses, (4) Active Beacons, (5) Global Positioning Systems, (6) Landmark Navigation, and (7) Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this paper serve only to represent their respective categories; they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevity, not all could be cited in this paper. The appendix contains a tabular comparison of the positioning systems discussed in this review that includes system and description, features, accuracy (position), accuracy (orientation), effective range, and source of information. (47 refs.)

RoboCup: A Challenge Problem for AI

Abstract: The Robot World-Cup Soccer (RoboCup) is an attempt to foster AI and intelligent robotics research by providing a standard problem where a wide range of technologies can be integrated and examined. The first RoboCup competition will be held at the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan. A robot team must actually perform a soccer game, incorporating various technologies, including design principles of autonomous agents, multiagent collaboration, strategy acquisition, real-time reasoning, robotics, and sensor fusion. RoboCup is a task for a team of multiple fast-moving robots under a dynamic environment. Although RoboCup's final target is a world cup with real robots, RoboCup offers a software platform for research on the software aspects of RoboCup. This article describes technical challenges involved in RoboCup, rules, and the simulation environment.

Virtual model control of a bipedal walking robot

Abstract: The transformation from high level task specification to low level motion control is a fundamental issue in sensorimotor control in animals and robots. This paper describes a control scheme called virtual model control that addresses this issue. Virtual model control is a motion control language that uses simulations of imagined mechanical components to create forces, which are applied through real joint torques, thereby creating the illusion that the virtual components are connected to the robot. Due to the intuitive nature of this technique, designing a virtual model controller requires the same skills as designing the mechanism itself. A high level control system can be cascaded with the low level virtual model controller to modulate the parameters of the virtual mechanisms. Discrete commands from the high level controller would then result in fluid motion. Virtual model control has been applied to a physical bipedal walking robot. A simple algorithm utilizing a simple set of virtual components has successfully compelled the robot to walk continuously over level terrain.

Cooperative search and rescue with a team of mobile robots

Abstract: We present an implemented algorithm for a distributed team of autonomous mobile robots to search for an object. When one robot finds it, they all gather around it, and then manipulate ("rescue") it. The algorithm exploits parallelism, with all robots searching concurrently, and also teamwork, because the manipulation is performed cooperatively. Our algorithm is fully distributed; the robots communicate with each other, and there is no central server or supervisor. Applications include hazardous waste cleanup, bomb detection and removal, materials delivery, and eventually the rescue of survivors of accidents or disasters. The search and rescue program was written using MOVER, a programming system for distributed tasks. The system provides high-level programming constructs for task distribution across robots. Finally, MOVER encourages code re-use because the task distribution mechanism can synchronize any set of procedures (without rewriting), allowing the programmer of a distributed task to access libraries of robot software written for single-robot tasks.

Application of rubber artificial muscle manipulator as a rehabilitation robot

Abstract: The application of a robot to rehabilitation has become a matter of great concern. This paper deals with functional recovery therapy, one important aspect of physical rehabilitation. Single-joint therapy machines have already been achieved. However, for more efficient therapy, multjoint robots are necessary to achieve more realistic motion patterns. This kind of robot must have a high level of safety for humans. A pneumatic actuator may be available for such a robot, because of the compliance of compressed air. A pneumatic rubber artificial muscle manipulator has been applied to construct a therapy robot with two degrees of freedom (DOF). Also, an impedance control strategy is employed to realize various motion modes for the physical therapy modes. Further, for efficient rehabilitation, it is desirable to comprehend the physical condition of the patient. Thus, the mechanical impedance of the human arm is used as an objective evaluation of recovery, and an estimation method is proposed. Experiments show the suitability of the proposed rehabilitation robot system.

Sensor fusion for mobile robot navigation

Abstract: We review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms, and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks.

Sensory-based motion planning with global proofs

Abstract: We present DistBug, a new navigation algorithm for mobile robots which exploits range data. The algorithm belongs to the Bug family, which combines local planning with global information that guarantees convergence. Most Bug-type algorithms use contact sensors and consist of two reactive modes of motion: moving toward the target between obstacles and following obstacle boundaries, DistBug uses range data in a new "leaving condition" which allows the robot to abandon obstacle boundaries as soon as global convergence is guaranteed, based on the free range in the direction of the target. The leaving condition is tested directly on the sensor readings, thus making the algorithm simple to implement. To further improve performance, local information is utilized for choosing the boundary following direction, and a search manager is introduced for bounding the search area. The simulation results indicate a significant advantage of DistBug relative to the classical Bug2 algorithm. The algorithm was implemented and tested on a real robot, demonstrating the usefulness and applicability of our approach.

Many Robots Make Short Work

Abstract: Keywords: OAA ; mobile robots ; [VRAI] Note: Paper decribing the AAAI competition Reference LSRO2-ARTICLE-1997-003 Record created on 2005-02-04, modified on 2017-05-10

Robot Shaping: An Experiment in Behavior Engineering

Abstract: From the Publisher: foreword by Lashon Booker "[This] book gives a clear and comprehensive exposition of [the authors] extensive experience in integrating reinforcement learning and autonomous robotics. Their continuing contribution is to the development of a distinct engineering discipline (`Behavior engineering') through which such robots can be created. I am excited because their efforts combine some of the best theoretical ideas with a strong eye for the practical - for what will actually work." -- Stewart W. Wilson, The Rowland Institute for Science To program an autonomous robot to act reliably in a dynamic environment is a complex task. The dynamics of the environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through interaction with its environment and then adapt its behavior, greatly simplifies the designer's work. A learning robot need not be given all of the details of its environment, and its sensors and actuators need not be finely tuned. Robot Shaping is about designing and building learning autonomous robots. The term "shaping" comes from experimental psychology, where it describes the incremental training of animals. The authors propose a new engineering discipline, "behavior engineering," to provide the methodologies and tools for creating autonomous robots. Their techniques are based on classifier systems, a reinforcement learning architecture originated by John Holland, to which they have added several new ideas, such as "mutespec," classifier system "energy," and dynamic population size. In the book they present Behavior Analysis and Training (BAT) as an example of a behavior engineering methodology.

A modular system for robust positioning using feedback from stereo vision

Abstract: This paper introduces a modular framework for robot motion control using stereo vision. The approach is based on a small number of generic motion control operations referred to as primitive skills. Each primitive skill uses visual feedback to enforce a specific task-space kinematic constraint between a robot end-effector and a set of target features. By observing both the end-effector and target features, primitive skills are able to position with an accuracy that is independent of errors in hand-eye calibration. Furthermore, primitive skills are easily combined to form more complex kinematic constraints as required by different applications. These control laws have been integrated into a system that performs tracking and control on a single processor at real-time rates. Experiments with this system have shown that it is extremely accurate, and that it is insensitive to camera calibration error. The system has been applied to a number of example problems, showing that modular, high precision, vision-based motion control is easily achieved with off-the-shelf hardware.

Stereo vision based mapping and navigation for mobile robots

Abstract: This paper describes a visually guided robot that can plan paths, construct maps and explore an indoor environment. The robot uses a trinocular stereo vision system to produce highly accurate depth images at 2 Hz allowing it to safely travel through the environment at 0.5 m/s. The algorithm integrates stereo vision, occupancy grid mapping, and potential field path planning techniques to form a robust and cohesive robotic system for mapping and navigation. Stereo vision is shown to be a viable alternative to active sensing devices such as sonar and laser range finders.

Multi-robot exploration of an unknown environment, efficiently reducing the odometry error

Abstract: This paper deals with the intelligent exploration of an unknown environment by autonomous robots. In particular, we present an algorithm and associated analysis for collaborative exploration using two mobile robots. Our approach is based on robots with range sensors limited by distance. By appropriate behavioural strategies, we show that odometry (motion) errors that would normally present problems for mapping can be severely reduced. Our analysis includes polynomial complexity bounds and a discussion of possible heuristics.

Finding an unpredictable target in a workspace with obstacles

Abstract: This paper introduces a visibility-based motion planning problem in which the task is to coordinate the motions of one or more robots that have omnidirectional vision sensors, to eventually "see" a target that is unpredictable, has unknown initial position, and is capable of moving arbitrarily feast. A visibility region is associated with each robot, and the goal is to guarantee that the target will ultimately lie in at least one visibility region. Both a formal characterization of the general problem and several interesting problem instances are presented. A complete algorithm for computing the motion strategy of the robots is also presented, and is based on searching a finite cell complex that is constructed on the basis of critical information changes. A few computed solution strategies are shown. Several bounds on the minimum number of needed robots are also discussed.

SYMORO+: A system for the symbolic modelling of robots

Abstract: This paper presents the software package SYMORO+ for the automatic symbolic modelling of robots. This package permits to generate the direct geometric model, the inverse geometric model, the direct kinematic model, the inverse kinematic model, the dynamic model, and the inertial parameters identification models.The structure of the robots can be serial, tree structure or containing closed loops. The package runs on Sun stations and PC computers, it has been developed under MATHEMATICA and C language. In this paper we give an overview of the algorithms used in the different models; the computational cost of the dynamic models of the PUMA robot are given.

Decentralized motion planning for multiple mobile robots: the cocktail party model

Abstract: This paper presents an approach for decentralized real-time motion planning for multiple mobile robots operating in a common 2-dimensional environment with unknown stationary obstacles. In our model, a robot can see (sense) the surrounding objects. It knows its current and its target‘s position, is able to distinguish a robot from an obstacle, and can assess the instantaneous motion of another robot. Other than this, a robot has no knowledge about the scene or of the paths and objectives of other robots. There is no mutual communication among the robots; no constraints are imposed on the paths or shapes of robots and obstacles. Each robot plans its path toward its target dynamically, based on its current position and the sensory feedback; only the translation component is considered for the planning purposes. With this model, it is clear that no provable motion planning strategy can be designed (a simple example with a dead-lock is discussed); this naturally points to heuristic algorithms. The suggested strategy is based on maze-searching techniques. Computer simulation results are provided that demonstrate good performance and a remarkable robustness of the algorithm (meaning by this a virtual impossibility to create a dead-lock in a “random” scene).

Active compliance in robotic surgery—the use of force control as a dynamic constraint

Abstract: Robotic surgery can be carried out automatically by using a robot to move the cutting tool under position control. However, although the surgeon can observe the procedure on a visual display and has the ability to stop the operation in an emergency, he has little direct contact with the task. An alternative approach is to involve the surgeon more directly, by his moving a robot using active force control. The robot is then used to allow motion in preprogrammed regions, by the surgeon back-driving the robot motors, while preventing motion in prohibited areas. This active constraint robot (or ACROBOT) is described in this paper applied to knee surgery, in which the knee bones are accurately machined to allow the fitting of prosthetic knee implants. The ACROBOT is, however, ideally suited to a range of surgical procedure, because it allows the surgeon to feel the forces exerted during cutting and take appropriate action. This ability to be in direct control, while being constrained to cut within a permitted region, enhances safety and makes the system more acceptable to the medical community. The system of programmable constraint also allows the ACROBOT to provide the traditional benefits of robot surgery, namely the ability to machine complex geometrical surfaces very accurately and to make repetitive motions tirelessly. The system also has a potential for minimally invasive procedures. In knee surgery, for example, the robot could operate through a small incision in the skin and excise a volume into which a small, specially designed, unicompartmental prosthesis could fit.

Interference as a tool for designing and evaluating multi-robot controllers

Abstract: Designing and implementing cooperative group behaviors for robots is considered something of a black art involving an extensive amount of reprogramming and parameter adjustment. What seems to be lacking is a pragmatic, practical, general-purpose tool that would both guide the design and structure the evaluation of controllers for distributed real-world multi-robot tasks. In this paper, we propose the use of interference. between robots as one such simple tool for designing and evaluating multi-robot controllers. We explore how key issues in multi-robot control can be addressed using interference, a directly measurable property of a multi-robot system. We discuss how behavior arbitration schemes, i.e., the choice of controllers, can be made and adjusted using interference. As an experimental example, we demonstrate three different implementations of a collection clean-up (foraging) task using four physical mobile robots, and present analyses of the experimental data gathered from trials of all three implementations.

Active mobile robot localization

Abstract: Localization is the problem of determining the position of a mobile robot from sensor data. Most existing localization approaches are passive, i.e., they do not exploit the opportunity to control the robot’s effectors during localization. This paper proposes an active localization approach. The approach provides rational criteria for (1) setting the robot’s motion direction (exploration), and (2) determining the pointing direction of the sensors so as to most efficiently localize the robot. Furthermore, it is able to deal with noisy sensors and approximative world models. The appropriateness of our approach is demonstrated empirically using a mobile robot in a structured office environment.

A Rubbertuator-based structure-climbing inspection robot

Abstract: We describe our progress on the development of ROBIN, a robotic inspector. ROBIN is a structure-climbing robot designed for man-made environments. It is intended to carry cameras and other sensors onto man-made structures such as bridges, buildings, aircraft and ships for inspection. The robot has two vacuum fixtures connected by a 4 degree-of-freedom articulated mechanism that together allow it to walk across surfaces and will permit transition between adjacent surfaces. ROBIN is novel in several areas. It is the only climbing robot that uses McKibben type pneumatic muscles for movement. It is also novel in its use of a subsumption architecture controller in a climbing robot. ROBIN is one of the few climbing robots that is equipped with a mechanism that is capable of transitions between surfaces or from a horizontal surface to a vertical surface below.

Learning tasks from a single demonstration

Abstract: Learning a complex dynamic robot manoeuvre from a single human demonstration is difficult. This paper explores an approach to learning from demonstration based on learning an optimization criterion from the demonstration and a task model from repeated attempts to perform the task, and using the learned criterion and model to compute an appropriate robot movement. A preliminary version of the approach has been implemented on an anthropomorphic robot arm using a pendulum swing up task as an example.

Cooperative multi-robot observation of multiple moving targets

Abstract: An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of monitoring, or observing, the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement-determining where sensors should be located to maintain the targets in view. In complex applications of this type, the use of multiple sensors dynamically moving over time is required. In this paper, we investigate the use of a cooperative team of autonomous sensor-based robots for multi-robot observation of multiple moving targets. We focus primarily on developing the distributed control strategies that allow the robot team to attempt to maximize the collective time during which each object is being observed by at least one robot in the area of interest. Our initial efforts in this problem address the aspects of distributed control in homogeneous robot teams with equivalent sensing and movement capabilities working in an uncluttered, bounded area. This paper first formalizes the problem, discusses related work, and then shows that this problem is NP-hard. We then present a distributed approximate approach to solving this problem that combines low-level multi-robot control with higher-level control. The low-level control is described in terms of force fields emanating from the targets and the robots. The higher level control is presented in the ALLIANCE formalism, which provides mechanisms for fault tolerant cooperative control, and allows robot team members to adjust their low-level actions based upon the actions of their teammates. We then present the results of the implementation of portions of our approach, both in simulation and on physical robots.

Building a global map of the environment of a mobile robot: the importance of correlations

Abstract: The work presented in this paper is aimed at evaluating the influence of correlations between map entities on the process of robot relocation and global map building of the environment of a mobile robot navigating in an indoor environment. An EKF filter approach, supported by a probabilistic model to represent uncertain geometric information, is used to process the information obtained by the sensors mounted on the robot. We have developed two approaches, first, considering the existence of correlations, and second assuming independence between entities of the map. We have experimented with the mobile robot MACROBE, using its laser rangefinder.