Organizational Unit:

Mobile Robot Laboratory

Permanent Link

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

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Organizational Unit

College of Computing

ArchiveSpace Name Record

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

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Publication Search Results

Now showing 1 - 9 of 9

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.
Characterizing Performance Guarantees for Multiagent, Real-Time Systems Operating in Noisy and Uncertain Environments

(Georgia Institute of Technology, 2012) Lyons, Damian M. ; Arkin, Ronald C. ; Fox, Stephen ; Jiang, Shu ; Nirmal, Prem ; Zafar, Munzir

Autonomous robots offer the potential to conduct Counter- Weapons of Mass Destruction (C-WMD) missions in an efficient and robust manner. However, to leverage this potential, a mission designer needs to be able to determine how well a robot system will operate in the noisy and uncertain environments that a C-WMD mission may require. We are developing a software framework for verification of performance guarantees for C-WMD missions based on the MissionLab software system and a novel process algebra approach to representing robot programs and operating environments. In this paper, we report on our initial research for the Defense Threat Reduction Agency (DTRA) in understanding what is required from a performance guarantee to give a mission designer the information necessary to understand how well a robot program will perform in a specific environment. We link this to prior work on metrics for robot performance. Using a simple mission scenario, we explore the implications of uncertainty in the four components of the problem: the robot program, and the sensors, actuators and environment with which the program is executed.
Getting it Right the First Time: Predicted Performance Guarantees from the Analysis of Emergent Behavior in Autonomous and Semi-autonomous Systems

(Georgia Institute of Technology, 2012) Arkin, Ronald C. ; Lyons, Damian M. ; Jiang, Shu ; Nirmal, Prem ; Zafar, Munzir

A crucially important aspect for mission-critical robotic operations is ensuring as best as possible that an autonomous system be able to complete its task. In a project for the Defense Threat Reduction Agency (DTRA) we are developing methods to provide such guidance, specifically for counter-Weapons of Mass Destruction (C-WMD) missions. In this paper, we describe the scenarios under consideration, the performance measures and metrics being developed, and an outline of the mechanisms for providing performance guarantees.
Verifying Performance for Autonomous Robot Missions with Uncertainty

(Georgia Institute of Technology, 2012) Lyons, Damian M. ; Arkin, Ronald C. ; Liu, Tsung-Ming ; Jiang, Shu ; Nirmal, Paramesh

Establishing performance guarantees for robot missions is especially important for C-WMD applications. Software verification techniques, such as model checking (Clark 1999, Jhala & Majumdar 2009), can be applied to robotic applications but characteristics of this application area, including addition of a robot environment model and handling continuous spatial location well, exacerbate state explosion, a key weakness of these methods. We have proposed an approach to verifying robot missions that shifts the focus from state-based analysis onto the solution of a set of flow equations (Lyons et al. 2012). The key novelty introduced in this paper is a probabilistic spatial representation for flow equations. We show how this representation models the spatial situation for robot motion with environments or controllers that include discrete choice (constraints). A model such as we propose here is useful only if it can accurately predict robot motion. We conclude by presenting three validation results that show this approach has strong predictive power ; that is, that the verifications it produces can be trusted.