Organizational Unit:

Mobile Robot Laboratory

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https://hdl.handle.net/1853/70779

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Organizational Unit

College of Computing

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1110

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Publication Search Results

Now showing 1 - 10 of 13

Probabilistic Verification of Multi-robot Missions in Uncertain Environments

(Georgia Institute of Technology, 2015-11) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Harrington, Dagan ; Tang, Feng ; Tang, Peng

The effective use of autonomous robot teams in highly-critical missions depends on being able to establish performance guarantees. However, establishing a guarantee for the behavior of an autonomous robot operating in an uncertain environment with obstacles is a challenging problem. This paper addresses the challenges involved in building a software tool for verifying the behavior of a multi-robot waypoint mission that includes uncertain environment geometry as well as uncertainty in robot motion. One contribution of this paper is an approach to the problem of apriori specification of uncertain environments for robot program verification. A second contribution is a novel method to extend the Bayesian Network formulation to reason about random variables with different subpopulations, introduced to address the challenge of representing the effects of multiple sensory histories when verifying a robot mission. The third contribution is experimental validation results presented to show the effectiveness of this approach on a two-robot, bounding overwatch mission.
Mixed-Initiative Human-Robot Interaction: Definition, Taxonomy, and Survey

(Georgia Institute of Technology, 2015-10) Jiang, Shu ; Arkin, Ronald C.

The objectives of this article are: 1) to present a taxonomy for mixed-initiative human-robot interaction and 2) to survey its state of practice through the examination of past research along each taxonomical dimension. The paper starts with some definitions of mixed-initiative interaction (MII) from the perspective of human-computer interaction (HCI) to introduce the basic concepts of MII. We then synthesize these definitions to the robotic context for mixed-initiative human-robot teams. A taxonomy for mixed-initiative in human-robot interaction is then presented. The goal of the taxonomy is to inform the design of mixed-initiative human-robot systems by identifying key elements of these systems. The state of practice of mixed-initiative human-robot interaction is then surveyed and examined along each taxonomical dimension.
Performance Verification for Behavior-Based Robot Missions

(Georgia Institute of Technology, 2015-06) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Liu, Tsung-Ming ; Nirmal, Paramesh

Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means the state-space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian Network. Validation results are presented for the verification of a multiple-waypoint and an autonomous exploration robot mission.
SLAM-Based Spatial Memory for Behavior-Based Robots

(Georgia Institute of Technology, 2015) Jiang, Shu ; Arkin, Ronald C.

Knowledge is essential for an autonomous robot to act intelligently when tasked with a mission. With recent leaps of progress, the paradigm of SLAM (Simultaneous Localization and Mapping) has emerged as an ideal source of spatial knowledge for autonomous robots. However, despite advancements in both paradigms of SLAM and robot control, research in the integration of these areas has been lacking and remained open to investigation. This paper presents an integration of SLAM into a behavior-based robotic system as a dynamically acquired spatial memory, which can be used to enable new behaviors and augment existing ones. The effectiveness of the integrated system is demonstrated with a biohazard search mission, where a robot is tasked to search and locate a biohazard within an unknown environment under a time constraint.
Automatic Verification of Autonomous Robot Missions

(Georgia Institute of Technology, 2014) O'Brien, Matthew ; Arkin, Ronald C. ; Harrington, Dagan ; Lyons, Damian M. ; Jiang, Shu

Before autonomous robotics can be used for dangerous or critical missions, performance guarantees should be made available. This paper overviews a software system for the verification of behavior-based controllers in context of chosen hardware and environmental models. Robotic controllers are automatically translated to a process algebra. The system comprising both the robot and the environment are then evaluated by VIPARS, a verification software module in development, and compared to specific performance criteria. The user is returned a probability that the performance criteria will hold in the uncertainty of real-world conditions. Experimental results demonstrate accurate verification for a mission related to the search for a biohazard.
Verifying and Validating Multirobot Missions

(Georgia Institute of Technology, 2014) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Harrington, Dagan ; Liu, Tsung-Ming

We have developed an approach that can be used by mission designers to determine whether or not a performance guarantee for their mission software, when carried out under the uncertain conditions of a real-world environment, will hold within a threshold probability. In this paper we demonstrate its utility for verifying multirobot missions, in particular a bounding overwatch mission.
Getting it Right the First Time: Verification of Behavior-based Multirobot Missions

(Georgia Institute of Technology, 2014) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Harrington, Dagan ; O'Brien, Matthew

In research being conducted for the Defense Threat Reduction Agency (DTRA), we are concerned with robot missions that may only have a single opportunity for successful completion, with serious consequences if the mission is not completed properly. In particular we are investigating missions for Counter-Weapons of Mass Destruction (C-WMD) operations, which require discovery of a WMD within a structure and then either neutralizing it or reporting its location and existence to the command authority. Typical scenarios consist of situations where the environment may be poorly characterized in advance in terms of spatial layout, and have time-critical performance requirements. It is our goal to provide reliable performance guarantees for whether or not the mission as specified may be successfully completed under these circumstances, and towards that end we have developed a set of specialized software tools to provide guidance to an operator/commander prior to deployment of a robot tasked with such a mission.
Performance Guarantees for C - WMD Robot Missions

(Georgia Institute of Technology, 2013) Jiang, Shu ; Arkin, Ronald C. ; Lyons, Damian M. ; Liu, Tsung-Ming ; Harrington, Dagan

Robotics has been considered as one of the five key technology areas for defense against attacks with weapons of mass destruction (WMD). However, due to the mass impact nature of WMD, failures of counter-WMD (C-WMD) missions can have catastrophic consequences. To ensure robots’ success in carrying out C-WMD missions, we have developed a novel verification framework in providing performance guarantees for behavior-based and probabilistic robot algorithms in complex real-world environments. This paper describes the system architecture and discusses how the verification framework can be used to provide pre-mission performance guarantees for robots in executing C-WMD missions.
Performance Verification for Behavior-based Robot Missions

(Georgia Institute of Technology, 2013) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Liu, Tsung-Ming ; Nirmal, Paramesh ; Deeb, J.

Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. This requirement raises many issues for existing approaches to software verification. An approach based on behavior-based controllers in a process-algebra framework is proposed by Lyons et al [15] to side-step state combinatorics. In this paper we show that this approach can be used to generate a Dynamic Bayesian Net work for the problem, and that verification is reduced to a filtering problem for this network. We present validation results for the verification of a multiple waypoint robot mission using this approach.
Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty

(Georgia Institute of Technology, 2013) Lyons, Damian M. ; Arkin, Ronald C. ; Nirmal, P. ; Jiang, Shu ; Liu, Tsung-Ming ; Deeb, J.

Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behavior-based controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.