Michael J. S. Pelican

Coordinated deployment of multiple, heterogeneous robots

To be truly useful, mobile robots need to be fairly autonomous and easy to control. This is especially true in situations where multiple robots are used, due to the increase in sensory information and the fact that the robots can interfere with one another. The paper describes a system that integrates autonomous navigation, a task executive, task planning, and an intuitive graphical user interface to control multiple, heterogeneous robots. We have demonstrated a prototype system that plans and coordinates the deployment of teams of robots. Testing has shown the effectiveness and robustness of the system, and of the coordination strategies in particular.

Self-adaptive software for hard real-time environments

Researchers in the Automated Reasoning group at the Honeywell Technology Center and at the University of Michigan are developing adaptive intelligent software for high-risk situations. We are building a system called Self-Adaptive CIRCA (based on our cooperative intelligent real-time control architecture model) that combines the assurance of hard real-time systems with the self-modeling, self-monitoring, and self-modifying capabilities of self-adaptive software. The article describes elements of the system that are working now, as well as new components that we are still in the process of designing and building.

Exploiting Implicit Representations in Timed Automaton Verification for Controller Synthesis

Automatic controller synthesis and verification techniques promise to revolutionize the construction of high-confidence software. However, approaches based on explicit state-machine models are subject to extreme state-space explosion and the accompanying scale limitations. In this paper, we describe how to exploit an implicit, transition-based, representation of timed automata in controller synthesis. The CIRCA Controller Synthesis Module (CSM) automatically synthesizes hard real-time, reactive controllers using a transition-based implicit representation of the state space. By exploiting this implicit representation in search for a controller and in a customized model checking verifier, the CSM is able to efficiently build controllers for problems with very large state spaces. We provide experimental results that show substantial speed-up and orders-of-magnitude reductions in the state spaces explored. These results can be applied to other verification problems, both in the context of controller synthesis and in more traditional verification problems.

Using model checking to guarantee safety in automatically-synthesized real-time controllers

Concerns the development of autonomous, flexible control systems for mission-critical applications such as unmanned aerial vehicles (UAV) and deep space probes. These applications require hybrid real-time control systems, capable of effectively managing both discrete and continuous controllable parameters to maintain system safety and achieve system goals. Using the CIRCA architecture and its state space planner (SSP) for adaptive real-time control systems, these controllers are synthesized automatically and dynamically, online, while the platform is operating. Unlike many other AI planning systems, CIRCAs automatically-generated control plans have strong temporal semantics and provide safety guarantees, ensuring that the controlled system will avoid all forms of mission-critical failure. This paper is intended to convey an intuitive, qualitative understanding of the way CIRCA verifies its plans using model checking techniques.

Building Coordinated Real-Time Control Plans

We are interested in developing multi-agent systems that can provide real-time performance guarantees for critical missions that require cooperation. In particular, we are developing methods for teams of CIRCA agents to build coordinated plans that include explicit runtime communications to support distributed real-time reactivity to the environment. These teams can build plans in which different agents use their unique capabilities to guarantee that the team will respond in a coordinated fashion to mission-critical events. By reasoning explicitly about different agent roles, the agents can identify what communications must be exchanged in different situations. And, by reasoning explicitly about domain deadlines and communication time, the agents can build reactive plans that provide end-to-end performance guarantees spanning multi-agent teams.

MACBETH: a multi-agent constraint-based planner [autonomous agent tactical planner]

MACBETH is a constraint-based tactical planning engine for multi-agent teams. MACBETH is designed for domains in which a human user must quickly specify a mission to a team of autonomous agents. In these domains, it is more important to rapidly and accurately tailor existing plans to novel situations than to devise totally new plans. To this end, MACBETH combines hierarchical task network planning with modem constraint reasoning techniques, into a mixed-initiative planning system. This mixed-initiative planning system is driven by a graphical user interface inspired by a playbook metaphor, to generate, check and modify plans for teams of heterogeneous agents. MACBETH has been tested in two robotics domains: unmanned combat aerial vehicles (UCAV) sorties and tactical mobile robotics (TMR).

Incremental Verification for On-the-Fly Controller Synthesis

The CIRCA system automatically synthesizes hard real-time discrete event controllers from plant and environment descriptions. CIRCAs automatically-synthesized controllers provide guaranteed real-time performance and safety preservation in adversarial, non-closed-world domains. By separating controller construction from formal controller verification, CIRCA makes controller synthesis decisions in a time-abstract state space that is quite compact. However, controller verification requires a more complete consideration of time, to make real-time performance guarantees. By retaining information between verifications of partial controllers during the controller synthesis process, the incremental verification methods that we present here dramatically reduce the complexity of controller synthesis. We provide formal characterizations of our incremental verification technique and performance results demonstrating up to a 97% reduction in controller synthesis time using these methods.

Planning with increasingly complex executive models

We are developing autonomous control systems for mission-critical domains that require hard real-time performance guarantees. To automatically build reactive plans that meet these requirements, we use formal verification (model checking) techniques to assess the quality of plans as they are built. The verification process uses precise timed automaton models of the executive that will run the resulting reactive plan. This reflexive modeling allows our system to formally verify not just that its plans are correct, but that they will be executed correctly.

Embedding planning technology into satellite systems

Satellites will need increasing amounts of autonomy in order to maximize their mission capabilities even in the face of events that may disrupt their systems. This paper describes an on-board planning and execution system for satellites that schedules system tasks and responds to real-time events. The system consists of a mission planner that schedules nominal activities, a threat response planner that schedules actions to mediate external threats to the satellite and its mission, and an executive that takes the resulting plan and commands the satellite subsystems. A state-based simulation of a satellite system was developed and used to demonstrate the planning and execution system. I. Introduction There is an increasing need to develop on-board autonomy for satellite systems, both to increase their productivity and to protect them from hazards and threats such as component faults, approaching space debris, and dangerous space weather. We are developing an integrated system that demonstrates solutions to many of the challenges inherent in developing embedded planning systems for satellites. The Highly Autonomous Mission Manager for Event Response (HAMMER) system is designed to allow a satellite to operate and respond to threats even when it is not in communication with the ground or when time constraints require immediate response to threats. The HAMMER system attempts to meet mission objectives even in the face of threats. HAMMER prioritizes multiple, competing user goals and requests and determines an optimal ordering of satellite tasks to conserve resources and maximize capability. End user goals and requests are expected to come to the satellite asynchronously as the satellite is operating. Thus, new task schedules will need to be generated on-the-fly. Threats are also expected occur asynchronously and require on-the-fly replanning to counter the threats and still attempt to meet mission objectives. User requests will be at a high level (e.g., take an image of location X by time Y and download to location Z) and will need to be turned into a detailed plan of low-level satellite actions. The tight coupling between end user goals, mission planning, threat response, and task execution is a key challenge for these systems. HAMMER integrates an on-board execution system with two different on-board planning and scheduling systems: a Mission Planner (MP) that plans optimal sequences of actions to achieve mission goals, and a Threat Response Planner (TRP) that refines the mission plan with pre-planned responses to threats. The benefits of the HAMMER system are that it: 1) can receive high-level end user goals and produce optimal satellite plans; 2) can respond to threats without ground intervention; 3) is scalable and reusable because the core components are model-driven.

A high-level “tasking” interface for uninhabited combat air vehicles

The HCI debate over direct manipulation vs. automated agents shows a fundamental: humans want to remain in charge even if they don’t want to (or can’t) make every action and decision themselves. We have been exploring a middle road through the development of “tasking interfaces” to enable human operators to flexibly “call plays” (that is, stipulate plans) at various levels, leaving the remainder to be fleshed out by a planning system.