Hot-swapping robot task goals in reactive formal synthesis

Springer Tracts in Advanced Robotics

Prabhakar

2016

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We consider the problem of synthesizing controllers automatically for distributed robots that are loosely coupled using a formal synthesis approach. Formal synthesis entails construction of game strategies for a discrete transition system such that the system under the strategy satisfies a specification, given for instance in linear temporal logic (LTL). The general problem of automated synthesis for distributed discrete transition systems suffers from state-space explosion because the combined state-space has size exponential in the number of subsystems. Motivated by multi-robot motion planning problems, we focus on distributed systems whose interaction is nearly decoupled, allowing the overall specification to be decomposed into specifications for individual subsystems and a specification about the joint system. We treat specifically reactive synthesis for the GR(1) fragment of LTL. Each robot is subject to a GR(1) formula, and a safety formula describes constraints on their interaction. We propose an approach wherein we synthesize strategies independently for each subsystem; then we patch the separate controllers around interaction regions such that the specification about the joint system is satisfied.

Section: Preliminariesmentioning

confidence: 99%

“…Definition 1 (adapted from [12]) A reach annotation on a strategy automaton A = (V, δ , L) for a GR(1) formula ϕ is a function RA : V → {0, . .…”

Section: Preliminariesmentioning

confidence: 99%

Decoupled Formal Synthesis for Almost Separable Systems with Temporal Logic Specifications

Springer Tracts in Advanced Robotics

Prabhakar

2016

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“…Thus we are motivated to patch a nominal control strategy synthesized with respect to this product of discrete abstractions. In recent work by the authors [7], algorithms have been proposed for patching strategies to recover correctness with respect to a changing specification. In Algorithm 2, we exploit these methods to incrementally patch a given strategy automaton based on time-annotated graphs that model component systems.…”

Section: Control Synthesis For Gr(1) Using Time-annotationmentioning

confidence: 99%

“…end if 19: end if 20: return A Patch() (Line 13) modifies the strategy automaton given a change in the specification, e.g., as described in [7].…”

mentioning

confidence: 99%

Time-annotated game graphs for synthesis from abstracted systems

2015 54th IEEE Conference on Decision and Control (CDC)

2015

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Abstract-The construction of discrete abstractions is a crucial part of many methods for control synthesis of hybrid systems subject to formal specifications. In general, the product of discrete abstractions may not be a discrete abstraction for the product of the underlying continuously-valued systems. Addressing this, we present a control synthesis method for transition systems that are built from components with uncertain timing characteristics. The new device, called here time-annotated game graphs, is demonstrated in a variety of examples. While it is applicable generally to parity games, we consider it in the context of control subject to GR(1) specifications. We show how a nominal strategy obtained without time knowledge can be modified to recover correctness when time information becomes available. The methods are applied to a brief case study of an aircraft electric power system.

Hot-swapping robot task goals in reactive formal synthesis

53rd IEEE Conference on Decision and Control

Murray

2014

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Abstract. We consider the problem of synthesizing robot controllers to realize a task that unpredictably changes with time. Tasks are formally expressed in the GR(1) fragment of temporal logic, in which some of the variables are set by an adversary. The task changes by the addition or removal of goals, which occurs online (i.e., at run-time). We present an algorithm for mending control strategies to realize tasks after the addition of goals, while avoiding global resynthesis of the strategy. Experiments are presented for a planar surveillance task in which new regions of interest are incrementally added. Run-times are empirically shown to be favorable compared to re-synthesizing from scratch. We also present an algorithm for mending control strategies for the removal of goals. While in this setting the original strategy is still feasible, our algorithm provides a more satisfying solution by "tightening loose ends." Both algorithms are shown to yield so-called reach annotations, and thus the control strategies are easily amenable to other algorithms concerning incremental synthesis, e.g., as in previous work by the authors for navigation in uncertain environments.