36 research outputs found
Low-Effort Specification Debugging and Analysis
Reactive synthesis deals with the automated construction of implementations
of reactive systems from their specifications. To make the approach feasible in
practice, systems engineers need effective and efficient means of debugging
these specifications.
In this paper, we provide techniques for report-based specification
debugging, wherein salient properties of a specification are analyzed, and the
result presented to the user in the form of a report. This provides a
low-effort way to debug specifications, complementing high-effort techniques
including the simulation of synthesized implementations.
We demonstrate the usefulness of our report-based specification debugging
toolkit by providing examples in the context of generalized reactivity(1)
synthesis.Comment: In Proceedings SYNT 2014, arXiv:1407.493
Robust Model Predictive Control for Signal Temporal Logic Synthesis
Most automated systems operate in uncertain or adversarial conditions, and have to be capable of reliably reacting to changes in the environment. The focus of this paper is on automatically synthesizing reactive controllers for cyber-physical systems subject to signal temporal logic (STL) specifications. We build on recent work that encodes STL specifications as mixed integer linear constraints on the variables of a discrete-time model of the system and environment dynamics. To obtain a reactive controller, we present solutions to the worst-case model predictive control (MPC) problem using a suite of mixed integer linear programming techniques. We demonstrate the comparative effectiveness of several existing worst-case MPC techniques, when applied to the problem of control subject to temporal logic specifications; our empirical results emphasize the need to develop specialized solutions for this domain
Robust Model Predictive Control for Signal Temporal Logic Synthesis
Most automated systems operate in uncertain or adversarial conditions, and have to be capable of reliably reacting to changes in the environment. The focus of this paper is on automatically synthesizing reactive controllers for cyber-physical systems subject to signal temporal logic (STL) specifications. We build on recent work that encodes STL specifications as mixed integer linear constraints on the variables of a discrete-time model of the system and environment dynamics. To obtain a reactive controller, we present solutions to the worst-case model predictive control (MPC) problem using a suite of mixed integer linear programming techniques. We demonstrate the comparative effectiveness of several existing worst-case MPC techniques, when applied to the problem of control subject to temporal logic specifications; our empirical results emphasize the need to develop specialized solutions for this domain
Online Horizon Selection in Receding Horizon Temporal Logic Planning
Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the current goal. We propose a receding horizon algorithm for reactive synthesis that automatically determines a path to the currently pursued goal at runtime, in response to a nondeterministic environment. This is achieved by allowing each short horizon to have multiple local goals, and determining which local goal to pursue based on the current global goal, currently perceived environment and a pre-computed invariant dependent on each global goal. We demonstrate the utility of this additional flexibility in grant-response tasks, using a search-and-rescue example. Moreover, we show that these goal-dependent invariants mitigate the conservativeness of the receding horizon approach
Model Predictive Control for Signal Temporal Logic Specification
We present a mathematical programming-based method for model predictive
control of cyber-physical systems subject to signal temporal logic (STL)
specifications. We describe the use of STL to specify a wide range of
properties of these systems, including safety, response and bounded liveness.
For synthesis, we encode STL specifications as mixed integer-linear constraints
on the system variables in the optimization problem at each step of a receding
horizon control framework. We prove correctness of our algorithms, and present
experimental results for controller synthesis for building energy and climate
control
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications
We address the problem of diagnosing and repairing specifications for hybrid
systems formalized in signal temporal logic (STL). Our focus is on the setting
of automatic synthesis of controllers in a model predictive control (MPC)
framework. We build on recent approaches that reduce the controller synthesis
problem to solving one or more mixed integer linear programs (MILPs), where
infeasibility of a MILP usually indicates unrealizability of the controller
synthesis problem. Given an infeasible STL synthesis problem, we present
algorithms that provide feedback on the reasons for unrealizability, and
suggestions for making it realizable. Our algorithms are sound and complete,
i.e., they provide a correct diagnosis, and always terminate with a non-trivial
specification that is feasible using the chosen synthesis method, when such a
solution exists. We demonstrate the effectiveness of our approach on the
synthesis of controllers for various cyber-physical systems, including an
autonomous driving application and an aircraft electric power system
Reactive mission and motion planning with deadlock resolution avoiding dynamic obstacles
In the near future mobile robots, such as personal robots or mobile manipulators, will share the workspace with other robots and humans. We present a method for mission and motion planning that applies to small teams of robots performing a task in an environment with moving obstacles, such as humans. Given a mission specification written in linear temporal logic, such as patrolling a set of rooms, we synthesize an automaton from which the robots can extract valid strategies. This centralized automaton is executed by the robots in the team at runtime, and in conjunction with a distributed motion planner that guarantees avoidance of moving obstacles. Our contribution is a correct-by-construction synthesis approach to multi-robot mission planning that guarantees collision avoidance with respect to moving obstacles, guarantees satisfaction of the mission specification and resolves encountered deadlocks, where a moving obstacle blocks the robot temporally. Our method provides conditions under which deadlock will be avoided by identifying environment behaviors that, when encountered at runtime, may prevent the robot team from achieving its goals. In particular, (1) it identifies deadlock conditions; (2) it is able to check whether they can be resolved; and (3) the robots implement the deadlock resolution policy locally in a distributed manner. The approach is capable of synthesizing and executing plans even with a high density of dynamic obstacles. In contrast to many existing approaches to mission and motion planning, it is scalable with the number of moving obstacles. We demonstrate the approach in physical experiments with walking humanoids moving in 2D environments and in simulation with aerial vehicles (quadrotors) navigating in 2D and 3D environments.Boeing CompanyUnited States. Office of Naval Research. Multidisciplinary University Research Initiative. SMARTS (N00014-09-1051)United States. Office of Naval Research (N00014-12-1-1000)National Science Foundation (U.S.). Expeditions in Computer Augmented Program Engineerin