136 citations · 169 across the 27 of their papers we have counts for
13 papers · 1 filter
Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems
Junya Ikemoto, Satoshi Maruyama, Kazumune Hashimoto
This paper proposes a deep reinforcement learning (DRL)-based event-triggered controller design for networked artificial pancreas (AP) systems. Although existing DRL-based AP contr…
Data-Driven Synthesis of Probabilistic Controlled Invariant Sets for Linear MDPs
Kazumune Hashimoto, Shunki Kimura, Kazunobu Serizawa +3
We study data-driven computation of probabilistic controlled invariant sets (PCIS) for safety-critical reinforcement learning under unknown dynamics. Assuming a linear MDP model, w…
Synthesis of Event-triggered Controllers for SIRS Epidemic Models
Lichen Ding, Kazumune Hashimoto, Shigemasa Takai
In this paper, we investigate the problem of mitigating epidemics by applying an event-triggered control strategy. We consider a susceptible-infected-removed-susceptible (SIRS) mod…
Bayesian Meta-Learning on Control Barrier Functions with Data from On-Board Sensors
Wataru Hashimoto, Kazumune Hashimoto, Akifumi Wachi +3
In this paper, we consider a way to safely navigate the robots in unknown environments using measurement data from sensory devices. The control barrier function (CBF) is one of the…
Signal Temporal Logic Meets Convex-Concave Programming: A Structure-Exploiting SQP Algorithm for STL Specifications
Yoshinari Takayama, Kazumune Hashimoto, Toshiyuki Ohtsuka
This study considers the control problem with signal temporal logic (STL) specifications. Prior works have adopted smoothing techniques to address this problem within a feasible ti…
STLCCP: Efficient Convex Optimization-based Framework for Signal Temporal Logic Specifications
Yoshinari Takayama, Kazumune Hashimoto, Toshiyuki Ohtsuka
Signal temporal logic (STL) is a powerful formalism for specifying various temporal properties in dynamical systems. However, existing methods, such as mixed-integer programming an…
Neural Controller Synthesis for Signal Temporal Logic Specifications Using Encoder-Decoder Structured Networks
Wataru Hashimoto, Kazumune Hashimoto, Masako Kishida +1
In this paper, we propose a control synthesis method for signal temporal logic (STL) specifications with neural networks (NNs). Most of the previous works consider training a contr…
A Lifting Approach to Learning-Based Self-Triggered Control with Gaussian Processes
Wang Zhijun, Kazumune Hashimoto, Wataru Hashimoto +1
This paper investigates the design of self-triggered control for networked control systems (NCS), where the dynamics of the plant is unknown apriori. To deal with the nature of the…
STL2vec: Signal Temporal Logic Embeddings for Control Synthesis With Recurrent Neural Networks
Wataru Hashimoto, Kazumune Hashimoto, Shigemasa Takai
In this paper, a method for learning a recurrent neural network (RNN) controller that maximizes the robustness of signal temporal logic (STL) specifications is presented. In contra…
Collaborative rover-copter path planning and exploration with temporal logic specifications based on Bayesian update under uncertain environments
Kazumune Hashimoto, Natsuko Tsumagari, Toshimitsu Ushio
This paper investigates a collaborative rover-copter path planning and exploration with temporal logic specifications under uncertain environments. The objective of the rover is to…
Learning-based Symbolic Abstractions for Nonlinear Control Systems
Kazumune Hashimoto, Adnane Saoud, Masako Kishida +2
Symbolic models or abstractions are known to be powerful tools for the control design of cyber-physical systems (CPSs) with logic specifications. In this paper, we investigate a no…
Control of Timed Discrete Event Systems with Ticked Linear Temporal Logic Constraints
Takuma Kinugawa, Kazumune Hashimoto, Toshimitsu Ushio
This paper presents a novel method of synthesizing a fragment of a timed discrete event system(TDES),introducing a novel linear temporal logic(LTL), called ticked LTL. The tick…
Learning self-triggered controllers with Gaussian processes
Kazumune Hashimoto, Yuichi Yoshimura, Toshimitsu Ushio
This paper investigates the design of self-triggered controllers for networked control systems (NCSs), where the dynamics of the plant is \textit{unknown} apriori. To deal with the…