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A Fully Automated Framework for Control of Linear Systems from Temporal Logic Specifications
TLDR
The solution to the problem of finding a feedback control law with polyhedral bounds and a set of initial states so that all trajectories of the closed loop system satisfy the formula consists of three main steps.
Abstraction and control for Groups of robots
TLDR
This paper focuses on planar fully actuated robots and proposes an abstraction based on the definition of a map from the configuration space Q of the robots to a lower dimensional manifold A, whose dimension is independent of the number of robots.
Optimal Control of Markov Decision Processes With Linear Temporal Logic Constraints
TLDR
A sufficient condition for a policy to be optimal is proposed, and a dynamic programming algorithm is developed that synthesizes a policy that is optimal for a set of LTL specifications.
Discrete abstractions for robot motion planning and control in polygonal environments
TLDR
This paper presents a computational framework for automatic generation of provably correct control laws for planar robots in polygonal environments using polygon triangulation and discrete abstractions to map continuous motion planning and control problems to computationally inexpensive problems on finite-state-transition systems.
Robustness analysis and tuning of synthetic gene networks
TLDR
This work proposes an approach for the analysis of a class of uncertain piecewise-multiaffine differential equation models that are well adapted to the experimental data currently available and present interesting mathematical properties that allow the development of efficient algorithms for solving robustness analyses and tuning problems.
Symbolic planning and control of robot motion [Grand Challenges of Robotics]
TLDR
The aim of symbolic control as is envisioned in this article is to enable the usage of methods of formal logic, languages, and automata theory for solving effectively complex planning problems for robots and teams of robots.
Optimal path planning for surveillance with temporal-logic constraints*
TLDR
This paper utilizes Büchi automata to produce an automaton (which can be thought of as a graph) whose runs satisfy the temporal-logic specification, and presents a graph algorithm that computes a run corresponding to the optimal robot path.
Q-Learning for robust satisfaction of signal temporal logic specifications
TLDR
This paper proposes an approximation of STL synthesis problems that can be solved via Q-learning, and derives some performance bounds for the policies obtained by the approximate approach.
LTL Control in Uncertain Environments with Probabilistic Satisfaction Guarantees
TLDR
The problem of generating a control policy for a Markov Decision Process (MDP) such that the probability of satisfying an LTL formula over its states is maximized can be reduced to the problem of creating a robot control strategy that maximizes the probability to accomplish a task.
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