6463761
Snapshots for semantic maps
A significant area of research in mobile robotics is in the local representation of a remote environment. In order to include a human in a mobile robot task it becomes important to present the remote information efficiently to a human. A relatively new approach to information presentation is semantic maps. Semantic maps provide more detail about an environment than typical maps because they are augmented by icons or symbols that provide meaning for places or objects of interest. In this paper we present snapshot technology as a means to take pictures from the real world and store them in a semantic map. To make the snapshots and semantic map available to an operator, we identify and discuss general attributes for useful displays and present a mixed reality 3D interface that meets the requirements. The interface and snapshot technology are validated through experiments in real and simulated environments.
12614052
Learning haptic feedback for guiding driver behavior
Information about the driving state can be conveyed to automobile drivers through force feedback signals sent via the pedals and steering wheel. Because the set of possible haptic signals and driver responses is huge, it is desirable to automatically learn which signals are most useful to drivers. Thus, it is instructive to explore how machine learning techniques can be used as a step in the design of a haptic interface system. In this paper, we present a learning algorithm that learns useful haptic feedback and apply the algorithm to learning feedback for automobile drivers. We present evidence to show that the algorithm is sensitive enough to learn useful feedback under some circumstances, but that its scope may be limited by people's ability to act as admittance controllers.
43673902
Coordinated target assignment and intercept for unmanned air vehicles
Presents an end-to-end solution to the battlefield scenario where M unmanned air vehicles are assigned to strike N known targets, in the presence of dynamic threats. The problem is decomposed into the subproblems of (1) cooperative target assignment, (2) coordinated UAV intercept, (3) path planning, and (4) feasible trajectory generation. The design technique is based on a hierarchical approach to coordinated control. Detailed simulation results are presented.
11363478
Learning To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and suggests, instead, the application of give-and-take principles of bargaining. We modify and analyze a satisficing algorithm based on (Karandikar et al., 1998) that is compatible with the bargaining perspective. This algorithm is a form of relaxation search that converges to a satisficing equilibrium without knowledge of game payoffs or other agents' actions. We then develop an M action, N player social dilemma that encodes the key elements of the Prisoner's Dilemma. This game is instructive because it characterizes social dilemmas with more than two agents and more than two choices. We show how several different multi-agent learning algorithms behave in this social dilemma, and demonstrate that the satisficing algorithm converges, with high probability, to a Pareto efficient solution in self play and to the single play Nash equilibrium against selfish agents. Finally, we present theoretical results that characterize the behavior of the algorithm.
17845810
A binary-categorization approach for classifying multiple-record Web documents using application ontologies and a probabilistic model
The amount of information available on the World Wide Web has been increasing dramatically in recent years. To enhance speedy searching and retrieving Web documents of interest, researchers and practitioners have partially relied on various information retrieval techniques. We propose a probabilistic model to classify Web documents into relevant documents and irrelevant documents with respect to a particular application ontology, which is a conceptual-model snippet of standard ontologies. Our probabilistic model is based on multivariate statistical analysis and is different from the conventional probabilistic information retrieval models. The experiments we have conducted on a set of representative Web documents indicate that the proposed probabilistic model is promising in binary-categorization of multiple-record Web documents.
1846400
Common metrics for human-robot interaction
This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.
12552187
Parallel algorithms for evaluating sequences of set-manipulation operations
Given an off-line sequence <italic>S</italic> of <italic>n</italic> set-manipulation operations, we investigate the parallel complexity of evaluating <italic>S</italic> (i.e., finding the response to every operation in <italic>S</italic> and returning the resulting set). We show that the problem of evaluating <italic>S</italic> is in <italic>NC</italic> for various combinations of common set-manipulation operations. Once we establish membership in <italic>NC</italic> (or, if membership in <italic>NC</italic> is obvious), we develop techniques for improving the time and/or processor complexity.
7411332
Planarity-Preserving Clustering and Embedding for Large Planar Graphs
In this paper we present a novel approach for cluster-based drawing of large planar graphs that maintains planarity. Our technique works for arbitrary planar graphs and produces a clustering which satisfies the conditions for compound-planarity (c-planarity). Using the clustering, we obtain a representation of the graph as a collection of O(log n) layers, where each succeeding layer represents the graph in an increasing level of detail. At the same time, the difference between two graphs on neighboring layers of the hierarchy is small, thus preserving the viewer’s mental map. The overall running time of the algorithm is O(n log n), where n is the number of vertices of graph G.
6093420
Secure Biometric Authentication for Weak Computational Devices
This paper presents computationally “lightweight” schemes for performing biometric authentication that carry out the comparison stage without revealing any information that can later be used to impersonate the user (or reveal personal biometric information). Unlike some previous computationally expensive schemes — which make use of slower cryptographic primitives — this paper presents methods that are particularly suited to financial institutions that authenticate users with biometric smartcards, sensors, and other computationally limited devices. In our schemes, the client and server need only perform cryptographic hash computations on the feature vectors, and do not perform any expensive digital signatures or public-key encryption operations. In fact, the schemes we present have properties that make them appealing even in a framework of powerful devices capable of public-key signatures and encryptions. Our schemes make it computationally infeasible for an attacker to impersonate a user even if the attacker completely compromises the information stored at the server, including all the server’s secret keys. Likewise, our schemes make it computationally infeasible for an attacker to impersonate a user even if the attacker completely compromises the information stored at the client device (but not the biometric itself, which is assumed to remain attached to the user and is not stored on the client device in any form).
5913284
Persistent Authenticated Dictionaries and Their Applications
We introduce the notion of persistent authenticated dictionaries, that is, dictionaries where the user can make queries of the type "was element e in set S at time t?" and get authenticated answers. Applications include credential and certificate validation checking in the past (as in digital signatures for electronic contracts), digital receipts, and electronic tickets. We present two data structures that can efficiently support an infrastructure for persistent authenticated dictionaries, and we compare their performance.
18652925
Planarity-preserving clustering and embedding for large planar graphs
In this paper we present a novel approach for cluster-based drawing of large planar graphs that maintains planarity. Our technique works for arbitrary planar graphs and produces a clustering which satisfies the conditions for compound-planarity (c-planarity). Using the clustering, we obtain a representation of the graph as a collection of O(log n) layers, where each succeeding layer represents the graph in an increasing level of detail. At the same time, the difference between two graphs on neighboring layers of the hierarchy is small, thus preserving the viewer's mental map. The overall running time of the algorithm is O(n log n), where n is the number of vertices of graph G.