Showing papers on "Mobile 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.

A frontier-based approach for autonomous exploration

Abstract: We introduce a new approach for exploration based on the concept of frontiers, regions on the boundary between open space and unexplored space. By moving to new frontiers, a mobile robot can extend its map into new territory until the entire environment has been explored. We describe a method for detecting frontiers in evidence grids and navigating to these frontiers. We also introduce a technique for minimizing specular reflections in evidence grids using laser-limited sonar. We have tested this approach with a real mobile robot, exploring real-world office environments cluttered with a variety of obstacles. An advantage of our approach is its ability to explore both large open spaces and narrow cluttered spaces, with walls and obstacles in arbitrary orientation.

Cooperative mobile robotics: antecedents and directions

Abstract: There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

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.

Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans

Abstract: A mobile robot exploring an unknown environment has no absolute frame of reference for its position, other than features it detects through its sensors. Using distinguishable landmarks is one possible approach, but it requires solving the object recognition problem. In particular, when the robot uses two-dimensional laser range scans for localization, it is difficult to accurately detect and localize landmarks in the environment (such as corners and occlusions) from the range scans. In this paper, we develop two new iterative algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment, that avoid the above problems. The first algorithm is based on matching data points with tangent directions in two scans and minimizing a distance function in order to solve the displacement between the scans. The second algorithm establishes correspondences between points in the two scans and then solves the point-to-point least-squares problem to compute the relative pose of the two scans. Our methods work in curved environments and can handle partial occlusions by rejecting outliers.

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.)

DAMN: a distributed architecture for mobile navigation

Abstract: An architecture is presented in which distributed task-achieving modules, or behaviours, cooperatively determine a mobile robot's path by voting for each of various possible actions. An arbiter then performs command fusion and selects that action which best satisfies the prioritized goals of the system, as expressed by these votes, without the need to average commands. Command fusion allows multiple goals and constraints to be considered simultaneously. Examples of implemented systems are given, and future research directions in command fusion are discussed.

Adaptive evolutionary planner/navigator for mobile robots

Abstract: Based on evolutionary computation (EC) concepts, we developed an adaptive evolutionary planner/navigator (EP/N) as a novel approach to path planning and navigation. The EP/N is characterized by generality, flexibility, and adaptability. It unifies off-line planning and online planning/navigation processes in the same evolutionary algorithm which 1) accommodates different optimization criteria and changes in these criteria, 2) incorporates various types of problem-specific domain knowledge, and 3) enables good tradeoffs among near-optimality of paths, high planning efficiency, and effective handling of unknown obstacles. More importantly, the EP/N can self-tune its performance for different task environments and changes in such environments, mostly through adapting probabilities of its operators and adjusting paths constantly, even during a robot's motion toward the goal.

Control of a nonholomic mobile robot: Backstepping kinematics into dynamics

Abstract: A dynamical extension that makes possible the integration of a kinematic controller and a torque controller for nonholonomic mobile robots is presented. A combined kinematic/torque control law is developed using backstepping, and asymptotic stability is guaranteed by Lyapunov theory. Moreover, this control algorithm can be applied to the three basic nonholonomic navigation problems: tracking a reference trajectory, path following, and stabilization about a desired posture. The result is a general structure for controlling a mobile robot that can accommodate different control techniques, ranging from a conventional computed-torque controller, when all dynamics are known, to robust-adaptive controllers if this is not the case. A robust-adaptive controller based on neural networks (NNs) is proposed in this work. The NN controller can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamics in the vehicle. On-line NN weight tuning algorithms that do not require off-line learning yet guarantee small tracking errors and bounded control signals are utilized. © 1997 John Wiley & Sons, Inc.

AuRA: Principles and Practice in Review

Abstract: This paper reviews key concepts of the Autonomous Robot Architecture (AuRA). Its structure, strengths, and roots in biology are presented. AuRA is a hybrid deliberative/ reactive robotic architecture that has been developed and refined over the past decade. In this article, particular focus is placed on the reactive behavioural component of this hybrid architecture. Various real world robots that have been implemented using this architectural paradigm are discussed, including a case study of a multiagent robotic team that competed and won the 1994 AAAI Mobile Robot Competition.

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.

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.

Design, control, and energetics of an electrically actuated legged robot

Abstract: To study the design, control and energetics of autonomous dynamically stable legged machines we have built a planar one-legged robot, the ARL Monopod. Its top running speed of 4.3 km/h (1.2 m/s) makes it the fastest electrically actuated legged robot to date. We adapted Raibert's control laws for the low power electric actuation necessary for autonomous locomotion and performed a detailed energetic analysis of our experiments. A comparison shows that the ARL Monopod with its 125 W average power consumption is more energy efficient than previously built robots.

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

The Saphira architecture: A design for autonomy

Abstract: Mobile robots, if they are to perform useful tasks and become accepted in open environments, must be fully autonomous. Autonomy has many different aspects ; here the focus is on three central ones: the ability to attend to another agent, to take advice about the environment, and to carry out assigned tasks. All three involve complex sensing and planning operations on the part of the robot, including the use of visual tracking of humans, coordination of motor controls, and planning. It is shown how these capabilities are integrated in the Saphira architecture, using the concepts of coordination of behaviour, coherence of modelling, and communication with other agents.

The autonomous mobile robot SENARIO: a sensor aided intelligent navigation system for powered wheelchairs

Abstract: The SENARIO project is develoing a sensor-aided intelligent navigation system that provides high-level navigational aid to users of powered wheelchairs. The authors discuss new and improved technologies developed within SENARIO concerning task/path planning, sensing and positioning for indoor mobile robots as well as user interface issues. The autonomous mobile robot SENARIO, supports semi- or fully autonomous navigation. In semi-autonomous mode the system accepts typical motion commands through a voice-activated or standard joystick interface and supports robot motion with obstacle/collision avoidance features. Fully autonomous mode is a superset of semi-autonomous mode with the additional ability to execute autonomously high-level go-to-goal commands. At its current stage, the project has succeeded in fully supporting semi-autonomous navigation, while experiments on the fully autonomous mode are very encouraging.

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.

Current and future perspective of Honda humamoid robot

Abstract: Noting that legged locomotion allows greater mobility than motion on wheels, the authors describe how they developed a biped robot capable of walking like a human. They discuss the leg's structure, dynamics etc. Ways of maintaining stability are considered. Areas on which future development efforts will be focussed are outlined.

Stable control of a simulated one-legged running robot with hip and leg compliance

Abstract: We present a control strategy for a simplified model of a one-legged running robot which features compliant elements in series with hip and leg actuators. For this model, proper spring selection and initial conditions result in "passive dynamic" operation close to the desired motion, without any actuation. However, this motion is not stable. Our controller is based on online calculations of the desired passive dynamic motion which is then parametrized in terms of a normalized "locomotion time". We show in simulation that the proposed controller stabilizes a wide range of velocities and is robust to modeling errors. It also tracks changes in desired robot velocity and remains largely passive despite a fixed set of springs, masses, and inertias. Comparisons of simulated runs with direct hip actuation show 95% hip actuation energy savings at 3 m/s. Such energy savings are critical for the power autonomy of electrically actuated legged robots.

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.

Visually-guided obstacle avoidance in unstructured environments

Abstract: This paper presents an autonomous vision-based obstacle avoidance system. The system consists of three independent vision modules for obstacle detection, each of which is computationally simple and uses a different criterion for detection purposes. These criteria are based on brightness gradients, RGB (red, green, blue) color, and HSV (hue, saturation, value) color, respectively. Selection of which modules are used to command the robot proceeds exclusively from the outputs of the modules themselves. The system is implemented on a small monocular mobile robot and uses very lour resolution images. It has been tested for over 200 hours in diverse environments.

Dynamic path modification for car-like nonholonomic mobile robots

Abstract: A method combining planning and reactive control for car-like nonholonomic mobile robots is discussed. Firstly, a "bubble" for a car-like mobile robot is defined as the locally reachable space from a given configuration considering the obstacles and using the appropriate metric. Then a flexible feasible trajectory, based on the elastic band concepts, is constructed. This trajectory is smoothed using Bezier curves satisfying a minimum curvature constraint, and a parameterization is proposed which satisfies the robot kinematics constraints.

Genetic algorithms for adaptive motion planning of an autonomous mobile robot

Abstract: This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and online motion planning. We first present a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are presented. Then, we discuss extensions of the GA for solving both path planning and trajectory planning simultaneously.

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).