21050185
A Framework and Architecture for Multirobot Coordination
In this paper, we present a framework and the software architecture for the deployment of multiple autonomous robots in an unstructured and unknown environment with applications ranging from scouting and reconnaissance, to search and rescue and manipulation tasks. Our software framework provides the methodology and the tools that enable robots to exhibit deliberative and reactive behaviors in autonomous operation, to be reprogrammed by a human operator at run-time, and to learn and adapt to unstructured, dynamic environments and new tasks, while providing performance guarantees. We demonstrate the algorithms and software on an experimental testbed that involves a team of car-like robots using a single omnidirectional camera as a sensor without explicit use of odometry.
5542960
Metrics for analysis and optimization of grasps and fixtures
We develop two quality measures for the analysis and optimization of grasps and fixtures. The first metric is a measure of stability and is obtained by analyzing the effect of small perturbations in the position of the grasped object or small disturbance forces on the grasped object The second metric is a measure of robustness to errors in the positions of the fixture elements. In addition, we explore the effect that the stiffness of the fixture elements has on these two quality measures and propose a design optimization approach to maximize stability and robustness to errors.
6879835
Calibrating an air-ground control system from motion correspondences
In this paper we consider the problem of controlling the motion of a vehicle moving on a ground plane based on aerial imagery. In the course of this work we propose a novel analysis of the relationship between the velocity of the vehicle on the ground plane and the velocity of its projection in the image. We show that this relationship provides information about a subset of the parameters of the homography relating the ground plane to the aerial image plane and describe how we can recover this relationship from available measurements.
15738427
A potential field based approach to multi-robot manipulation
We describe a framework for controlling and coordinating a group of robots for cooperative manipulation tasks. The framework enables a decentralized approach to planning and control. It allows the robots to approach the object, organize themselves into a formation that will trap the object, and then transport the object to the desired destination. Our controllers and planners are derived from simple potential fields and the hierarchical composition of potential fields. We show how these potential field based controllers and planners benefit complex group interactions, specifically for manipulating and transporting objects in the plane. Theoretically, we show how we can derive results on formation stability with potential field based controllers in many cases. Simulation results demonstrate successful application to a wide range of examples without showing sensitivity to parameters. Because the framework is decentralized at both trajectory generation level and the estimation and control agent level, our framework can potentially scale to groups of tens and hundreds of robots.
29516211
Control of Contact Interactions with Acatastatic Nonholonomic Constraints
A robot arm performs many tasks by interacting with objects or other robots in the environment. It is important for the robot arm to be able to exhibit controlled interactions with the objects and other robots. The contact motion between the robot arm and an object can be rolling, sliding, or separation. In this article, we address the problem of maintaining rolling contact between the robot arm and an external moving object. We assume that a nominal model of the motion of the moving object is available. The dynamic system that characterizes the motion of the robot arm and the moving object in this case is acatastatic and nonholonomic. We have designed a nonlinear feedback for the control of such a system that successfully maintains rolling contact. Simulation results are presented to demonstrate the effectiveness of the system.
7023425
A Paradigm for Dynamic Coordination of Multiple Robots
In this paper, we present a paradigm for coordinating multiple robots in the execution of cooperative tasks. The basic idea in the paper is to assign to each robot in the team, a role that determines its actions during the cooperation. The robots dynamically assume and exchange roles in a synchronized manner in order to perform the task successfully, adapting to unexpected events in the environment. We model this mechanism using a hybrid systems framework and apply it in different cooperative tasks: cooperative manipulation and cooperative search and transportation. Simulations and real experiments demonstrating the effectiveness of the proposed paradigm are presented.
35078097
An adaptive location management algorithm for mobile computing
In mobile computing mobile hosts or mobile units move randomly from one place to another within a well-defined geographical area. This requires some mechanism for identifying the exact location of a mobile host. Such mechanisms are usually referred to as location management and is one of the essential components for supporting mobility. In the past a number of efficient location management schemes have been suggested but they lack adaptability. We believe that an adaptable location management scheme is more desirable because of frequent change in the location of mobile hosts. In this paper, we report a location management algorithm, which adapts to the constant changing scenario. Our algorithm makes use of some of the concepts of location management schemes proposed in the past.
5480787
Parallel Formulations of Decision-Tree Classification Algorithms
Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. In this paper, we present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. We also provide the analysis of the cost of computation and communication of the proposed hybrid method. Moreover, experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.
10015251
Repartitioning of Adaptive Meshes: Experiments with Multilevel Diffusion
For a large class of irregular grid applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the graph evolves, the adapted mesh has to be repartitioned to ensure good load balance. If this new graph is partitioned from scratch, it will lead to an excessive migration of data among processors. In this paper, we present a new scheme for computing repartitionings of adaptively refined meshes. This scheme performs diffusion of vertices in a multilevel framework and minimizes vertex movement without significantly compromising the edge-cut.
12696238
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These discovered clusters are used to explain the characteristics of the data distribution. In this paper we propose a new methodology for clustering related items using association rules, and clustering related transactions using clusters of items. Our approach is linearly scalable with respect to the number of transactions. The frequent item-sets used to derive association rules are also used to group items into a hypergraph edge, and a hypergraph partitioning algorithm is used to nd the clusters. Our experiments indicate that clustering using association rule hypergraphs holds great promise in several application domains. Our experiments with stock-market data and congressional voting data show that this clustering scheme is able to successfully group items that belong to the same group. Clustering of items can also be used to cluster the transactions containing these items. Our experiments with congressional voting data show that this method is quite e ective in nding clusters of transactions that correspond to either democrat or republican voting patterns. Compared to the existing clustering algorithmAutoclass, our algorithm produced comparable quality clusters in the congressional voting data. This work was supported by NSF grant ASC-9634719, Army Research O ce contract DA/DAAH04-95-1-0538, Cray Research Inc. Fellowship, and IBM partnership award, the content of which does not necessarily re ect the policy of the government, and no ofcial endorsement should be inferred. Access to computing facilities was provided by AHPCRC, Minnesota Supercomputer Institute, Cray Research Inc., and NSF grant CDA-9414015. See http://www.cs.umn.edu/ han for an extended version of this paper and other related papers.
368036
Data Organization Issues for Location-Dependent Queries in Mobile Computing
We consider queries which originate from a mobile unit and whose result depends on the location of the user who initiates the query. Example of such a query is How many people are living in the region I am currently in?" We execute such queries based on location-dependent data involved in their processing. We build concept hierarchies based on the location data. These hierarchies define mapping among different granularities of locations. One such hierarchy is to generate domain knowledge about the cities that belong to a state. The hierarchies are used as distributed directories to assist in finding the database or relation that contains the values of the location-dependent attribute in a particular location. We extend concept hierarchies to include spatial indexes on the location-dependent attributes. Finally, we discuss how to partition and replicate relations based on the location to process the queries efficiently. We briefly discuss the implementation issues.