Engineering topics

Muscettola, Nicola

Publications and source records attributed to Muscettola, Nicola.

At least 19 records

NASA NTRS2006

Intelligent Rover Execution for Detecting Life in the Atacama Desert

On-board supervisory execution is crucial for the deployment of more capable and autonomous remote explorers. Planetary science is considering robotic explorers operating for long periods of time without ground supervision while interacting with a changing and often hostile environment. Effective and robust operations require on-board supervisory control with a high level of awareness of the principles of functioning of the environment and of the numerous internal subsystems that need to be coordinated. We describe an on-board rover executive that was deployed on a rover as past of the "Limits of Life in the Atacama Desert (LITA)" field campaign sponsored by the NASA ASTEP program. The executive was built using the Intelligent Distributed Execution Architecture (IDEA), an execution framework that uses model-based and plan-based supervisory control of its fundamental computational paradigm. We present the results of the third field experiment conducted in the Atacama desert (Chile) in August - October 2005.

Baskaran, Vijayakumar↗

NASA NTRS2006

Model-Unified Planning and Execution for Distributed Autonomous System Control

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Aschwanden, Pascal↗

NASA NTRS2005

Temporal Dynamic Controllability Revisited

An important issue for temporal planners is the ability to handle temporal uncertainty. We revisit the question of how to determine whether a given set of temporal requirements are feasible in the light of uncertain durations of some processes. In particular, we consider how best to determine whether a network is Dynamically Controllable, i.e., whether a dynamic strategy exists for executing the network that is guaranteed to satisfy the requirements. Previous work has shown the existence of a pseudo-polynomial algorithm for testing Dynamic Controllability. Here, we greatly simplify the previous framework, and present a true polynomial algorithm with a cutoff based only on the number of nodes.

Morris, Paul H.↗

NASA NTRS2005

Planner-Based Control of Advanced Life Support Systems

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster: simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods. We describe reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control. We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

Muscettola, Nicola↗

NASA NTRS2005

Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.

Muscettola, Nicola↗

NASA NTRS2004

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Muscettola, Nicola↗

NASA NTRS2004

Model-based Executive Control through Reactive Planning for Autonomous Rovers

This paper reports on the design and implementation of a real-time executive for a mobile rover that uses a model-based, declarative approach. The control system is based on the Intelligent Distributed Execution Architecture (IDEA), an approach to planning and execution that provides a unified representational and computational framework for an autonomous agent. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting agents, each with the same fundamental structure. We show that planning and real-time response are compatible if the executive minimizes the size of the planning problem. We detail the implementation of this approach on an exploration rover (Gromit an RWI ATRV Junior at NASA Ames) presenting different IDEA controllers of the same domain and comparing them with more classical approaches. We demonstrate that the approach is scalable to complex coordination of functional modules needed for autonomous navigation and exploration.

Finzi, Alberto↗

NASA NTRS2003

A Real-Time Rover Executive based On Model-Based Reactive Planning

This paper reports on the experimental verification of the ability of IDEA (Intelligent Distributed Execution Architecture) effectively operate at multiple levels of abstraction in an autonomous control system. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting control agents, each organized around the same fundamental structure. Two IDEA agents, a system-level agent and a mission-level agent, are designed and implemented to autonomously control the K9 rover in real-time. The system is evaluated in the scenario where the rover must acquire images from a specified set of locations. The IDEA agents are responsible for enabling the rover to achieve its goals while monitoring the execution and safety of the rover and recovering from dangerous states when necessary. Experiments carried out both in simulation and on the physical rover, produced highly promising results.

Bias, M. Bernardine↗

NASA NTRS2002

Computing the Envelope for Stepwise-Constant Resource Allocations

Computing tight resource-level bounds is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with nodes equal to the events and edges equal to the necessary predecessor links between events. A staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. Each stage has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible and promising for use in the inner loop of flexible-time scheduling algorithms.

Muscettola, Nicola↗

NASA NTRS2002

IDEA: Planning at the Core of Autonomous Reactive Agents

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Muscettola, Nicola↗

NASA NTRS2001

Dynamic Control of Plans with Temporal Uncertainty

Certain planning systems that deal with quantitative time constraints have used an underlying Simple Temporal Problem solver to ensure temporal consistency of plans. However, many applications involve processes of uncertain duration whose timing cannot be controlled by the execution agent. These cases require more complex notions of temporal feasibility. In previous work, various "controllability" properties such as Weak, Strong, and Dynamic Controllability have been defined. The most interesting and useful Controllability property, the Dynamic one, has ironically proved to be the most difficult to analyze. In this paper, we resolve the complexity issue for Dynamic Controllability. Unexpectedly, the problem turns out to be tractable. We also show how to efficiently execute networks whose status has been verified.

Morris, Paul↗

NASA NTRS2001

Verification of Plan Models Using UPPAAL

This paper describes work on the verification of HSTS, the planner and scheduler of the Remote Agent autonomous control system deployed in Deep Space 1 (DS1). The verification is done using UPPAAL, a real time model checking tool. We start by motivating our work in the introduction. Then we give a brief description of HSTS and UPPAAL. After that, we give a mapping of HSTS models into UPPAAL and we present samples of plan model properties one may want to verify. Finally, we conclude with a summary.

Khatib, Lina↗

NASA NTRS2001

Model Checking the Remote Agent Planner

This work tackles the problem of using Model Checking for the purpose of verifying the HSTS (Scheduling Testbed System) planning system. HSTS is the planner and scheduler of the remote agent autonomous control system deployed in Deep Space One (DS1). Model Checking allows for the verification of domain models as well as planning entries. We have chosen the real-time model checker UPPAAL for this work. We start by motivating our work in the introduction. Then we give a brief description of HSTS and UPPAAL. After that, we give a sketch for the mapping of HSTS models into UPPAAL and we present samples of plan model properties one may want to verify.

Khatib, Lina↗

NASA NTRS2001

Computing the Envelope for Stepwise Constant Resource Allocations

Estimating tight resource level is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with noises equal to the events and edges equal to the necessary predecessor links between events. The incremental solution of a staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. The staged algorithm has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible for use in the inner loop of search-based scheduling algorithms.

Muscettola, Nicola↗

NASA NTRS2000

Remote Agent Experiment

Remote Agent (RA) is a model-based, reusable artificial intelligence (At) software system that enables goal-based spacecraft commanding and robust fault recovery. RA was flight validated during an experiment on board of DS1 between May 17th and May 21th, 1999.

Benard, Doug↗

NASA NTRS2000

A Unified Approach to Model-Based Planning and Execution

Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.

Muscettola, Nicola↗

NASA NTRS2000

Executing Temporal Networks With Uncertainty

Simple Temporal Networks (STNs) have proved useful in applications that involve metric time. However, many applications involve events whose timing is uncertain in the sense that it is not controlled by the execution agent. In this paper we consider execution algorithms for temporal networks with events of uncertain duration. We present two such algorithms. The first retains maximum flexibility, but requires potentially costly updates during execution. The second surrenders some flexibility in order to obtain a fast execution comparable to that available for ordinary STNs.

Morris, Paul↗

NASA NTRS1999

Next Generation Remote Agent Planner

In May 1999, as part of a unique technology validation experiment onboard the Deep Space One spacecraft, the Remote Agent became the first complete autonomous spacecraft control architecture to run as flight software onboard an active spacecraft. As one of the three components of the architecture, the Remote Agent Planner had the task of laying out the course of action to be taken, which included activities such as turning, thrusting, data gathering, and communicating. Building on the successful approach developed for the Remote Agent Planner, the Next Generation Remote Agent Planner is a completely redesigned and reimplemented version of the planner. The new system provides all the key capabilities of the original planner, while adding functionality, improving performance and providing a modular and extendible implementation. The goal of this ongoing project is to develop a system that provides both a basis for future applications and a framework for further research in the area of autonomous planning for spacecraft. In this article, we present an introductory overview of the Next Generation Remote Agent Planner. We present a new and simplified definition of the planning problem, describe the basics of the planning process, lay out the new system design and examine the functionality of the core reasoning module.

Jonsson, Ari K.↗