We consider multi-robot systems that include sensor nodes and aerial or ground robots networked together. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in...
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ISBN:
(纸本)3540288163
We consider multi-robot systems that include sensor nodes and aerial or ground robots networked together. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We present a sensor network deployment method using autonomous aerial vehicles and describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for repair, to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.).
Given a continuous-time bandlimited signal, the Shannon sampling theorem provides an interpolation scheme for exactly reconstructing it from its discrete samples. We analyze the relationship between concentration (or ...
This paper investigates low-cost strategies for the multiagent object collection task, in which multiple agents work together to collect a set of items distributed throughout an environment. Several agent architecture...
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We present an architecture for complex affective robots for human-robot interaction. After describing our rationale for using affect as a means of "architectural integration", we give a quick conceptual exam...
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This paper is an examination of communication in hive-based swarms in the biological setting, focusing on the effect environmental factors have on the utility of communication. Our investigation utilizes a generationa...
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This paper is an examination of communication in hive-based swarms in the biological setting, focusing on the effect environmental factors have on the utility of communication. Our investigation utilizes a generational survival task to measure the benefit of communication in a biological setting. Swarm members forage for food, consuming energy in the process, and returning to a central "hive" to contribute any surplus. The resources of the hive determine when reproduction is possible, so it is in the best interest of the population to maximize the efficiency of foraging. The measure of performance is the size of the swarm surviving at the end of a simulation run. Each simulation begins with a swarm of fixed size (5 agents), making contributions to the hive (and subsequent procreation) necessary for good performance.
In this paper, we present APOC, an agent architecture framework intended for the analysis, comparison, and evaluation of agent architectures. We demonstrate how four main architectures, GRL, ICARUS, PRODIGY, and SOAR ...
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In this paper, we describe a new methodology for determining the utility of emotions. After briefly reviewing the status quo of emotional agents in AI, we describe the methodology and demonstrate it by showing the uti...
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Speaker recognition systems perform better when clean speech signals are used for the task. In the presence of high levels of background noise, speech recorded from a close speaking microphone will be degraded and hen...
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Speaker recognition systems perform better when clean speech signals are used for the task. In the presence of high levels of background noise, speech recorded from a close speaking microphone will be degraded and hence the performance of the speaker recognition system. Use of a transducer held at the throat results in a signal that is clean even in a noisy environment. This paper discusses the prospect of using such signals for speaker recognition. A study of a text-independent speaker recognition system based on features extracted from speech simultaneously recorded using a throat microphone and a close-speaking microphone in clean and simulated noisy conditions is conducted. Autoassociative neural networks are used to model the speaker characteristics based on the vocal tract system and excitation source features represented by weighted linear prediction cepstral coefficients and linear prediction residual, respectively. The results of experimental studies show that the speech collected from the throat microphone can be used for tasks like speaker recognition, especially in noisy conditions.
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