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Institute for Robotics and Intelligent Machines (IRIM)

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Author: Howard, Ayanna M. × End date: 2006 × Start date: 2000 × Has files: Yes ×

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Now showing 1 - 10 of 33
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An Imaging Technique for Safe Spacecraft Landing and Autonomous Hazard Avoidance

2006-07 , Jones, Brandon M. , Howard, Ayanna M.

The focus of this paper is to present an image transformation algorithm to interpret historical imagery land data for autonomous safe landing of a robotic spacecraft. Inherent geographical hazards of Martian terrain may impede safe landing for a science exploration spacecraft. Surface visualization software for hazard detection and avoidance may therefore be applied to enable an autonomous and intelligent spacecraft descent upon entering the planetary atmosphere. The methodology proposed involves integrating linear algebra and computer vision/graphics techniques, with the intrinsic parameters governing spacecraft dynamic motion and camera calibration, in order to assess hazards that might impede spacecraft landing. In this paper, we provide algorithmic details and simulation results of our methodology applied to a representative Mars landing descent profile.

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Role Allocation in Human-Robot Interaction Schemes for Mission Scenario Execution,

2006-05 , Howard, Ayanna M.

In this paper, we focus on the problem of maximizing system performance for future space exploration missions involving both human and robot agents. One of the main challenges in human-robot interaction scenarios is determining which tasks are best done with either human, robotic systems, or in collaboration with each. Such partitioning of the task space must acknowledge the capabilities of both agents, as well as incorporate the effect of repetitive workload, or stress, on the human operator. Our methodology for role allocation, which typically consists of either the human or the machine executing a single task, is based on predicting system performance of a given scenario by incorporating the concept of task switching. Task switching is defined as the process of alternating or switching attention between tasks when responding to a sequence of stimulus presentations. Using this concept, system performance can be predicted and used to determine an optimal allocation of tasks to be divided between human controlled and autonomous robotic systems to minimize mental workload while maximizing task performance. We provide details of the approach in this paper and present our results as applied to a simulated rendezvous/docking mission scenario.

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Multi-Robot Task Allocation in Lunar Mission Construction Scenarios

2005-10 , Thomas, George , Howard, Ayanna M. , Williams, Andrew B. , Moore-Alston, Aryen

In this paper, we propose a method for multirobot task allocation based on the concept of task decomposition for a lunar mission scenario. This methodology focuses on segmenting a task scenario into a sequence of operations called functional primitives that are defined a priori by a set of performance metrics and resource requirements. In real-time, multiple robotic agents determine their capabilities and skill sets associated with the defined functional primitives in order to determine a suitable allocation scheme. We discuss the methodology in detail, and provide results for a simulated lunar mission construction scenario using the Multi-Agent Robot Simulator for Lunar Construction (MARS-LC) system.

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A Methodology to Assess Performance of Human-Robotic Systems in Achievement of Collective Tasks

2005-08 , Howard, Ayanna M.

In this paper, we present a methodology to assess system performance of human-robotic systems in achievement of collective tasks such as habitat construction, geological sampling, and space exploration. The methodology uses a systematic approach that assesses performance by incorporating capabilities of both human and robotic agents based on accomplishment of functional operations and effect of cognitive stress due to continuous operation by the human agent. In this paper, we provide an overview of the assessment system and discuss its implementation on a representative habitat construction task.

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Fuzzy-Logic Based Selection of Surface Feature Observations for Small Body Proximity Operations

2006-07 , Howard, Ayanna M.

In this paper, we discuss the development of an autonomous system capable of maintaining surface feature references within sensor view by recommending spacecraft trajectory adjustments based on predefined criteria. The ability to localize with respect to terrain features is a necessary component for increasing the reliability of spacecraft position estimation during small body operations. The proposed algorithm uses the concept of fuzzy logic to maintain satisfaction of a number of feature selection criteria, which, when satisfied, allow consistent updating of feature observations. We provide details of the algorithm in this paper, and present results from integrating the algorithm into a small body descent simulator.

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A novel tiered sensor fusion approach for terrain characterization and safe landing assessment

2006-03 , Serrano, Navid , Bajracharya, Max , Howard, Ayanna M. , Seraji, Homayoun

This paper presents a novel, tiered sensor fusion methodology for real-time terrain safety assessment. A combination of active and passive sensors, specifically, radar, lidar, and camera, operate in three tiers according to their inherent ranges of operation. Low-level terrain features (e.g. slope, roughness) and high-level terrain features (e.g. hills, craters) are integrated using principles of reasoning under uncertainty. Three methodologies are used to infer landing safety: fuzzy reasoning, probabilistic reasoning, and evidential reasoning. The safe landing predictions from the three fusion engines are consolidated in a subsequent decision fusion stage aimed at combining the strengths of each fusion methodology. Results from simulated spacecraft descents are presented and discussed.

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A 3D Virtual Environment for Exploratory Learning in Mobile Robot Control

2005-10 , Howard, Ayanna M. , Paul, Wesley

This paper discusses a virtual environment that enables human agents to develop the skills necessary to control a mobile robot through the implementation of exploratory learning practices. The interface connects the human user to both a virtual and physical robot resident in the real-world, and allows evaluation of human performance using a framework that analyzes execution parameters during human operation. The execution data is then used to compare the capability of human agents to learn the skill sets necessary to control the robot during a novel task situation. We give an overview of the environment, as well as the experimental results comparing the performance of multiple operators learning to control a virtual robot.

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Adapting Human Leadership Approaches for Role Allocation in Human-Robot Navigation Scenarios

2006-07 , Howard, Ayanna M. , Cruz, Gerardo

In this paper, we propose to examine the practices of leadership defined in human relationships and model their use in maximizing performance for human-robot interaction scenarios. This process involves first defining the human-robot space of interaction and mapping the situational context in which human leadership styles are most fitting. We then determine which behavior, for both the human and robot, is most appropriate in order to understand the proper roles for human-robot integration. From there, we model the necessary robot behavior for increasing efficiency in human-robot interaction schemes. We conclude by discussing experimental results derived from allocating roles in representative human-robot navigation scenarios.

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A Human-Robot Mentor-Protégé Relationship to Learn Off-Road Navigation Behavior

2005-10 , Howard, Ayanna M. , Werger, Barry , Seraji, Homayoun

In this paper, we present an approach to transfer human expertise for learning off-road navigation behavior to an autonomous mobile robot. The methodology uses the concept of humanized intelligence to combine principal component analysis and neural network learning to embed human driving expertise onto mobile robots. The algorithms are tested in the field using a commercial Pioneer 2AT robot to demonstrate autonomous traversal over rough natural terrain.

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Mars exploration rover performance as a baseline for flight Rover autonomy technology assessment

2005-09 , Tunstel, Edward , Howard, Ayanna M. , Maimone, Mark , Trebi-Ollennu, Ashitey

Technology assessments rely on performance metrics to establish a basis for rating technologies. Metrics are also used to measure relative merit of similar technologies to state-of-the-art technology. Functional performance metrics are presented for mobility and robotic arm autonomy exercised on the Mars Exploration Rovers (MER) surface mission thus far. The metrics are used to apply an existing technology assessment method to establish a baseline for assessing future flight rover technologies. The methodology decomposes robotic activities into operational functions and addresses how technologies, based on performance metrics, can be systematically related to increases in science return. Considering the basic mission objective to maximize scientific yield, we can assess how relative performance of future technologies might impact science return. We provide a useful set of metrics and present an example application of the method to assess merit of hypothetical future Mars rover performance relative to the MER baseline.

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