18 citations · 23 across the 6 of their papers we have counts for
7 papers
Learning Locally, Communicating Globally: Reinforcement Learning of Multi-robot Task Allocation for Cooperative Transport
Kazuki Shibata, Tomohiko Jimbo, Tadashi Odashima +2
We consider task allocation for multi-object transport using a multi-robot system, in which each robot selects one object among multiple objects with different and unknown weights.…
Resilience Evaluation of Entropy Regularized Logistic Networks with Probabilistic Cost
Koshi Oishi, Yota Hashizume, Tomohiko Jimbo +2
The demand for resilient logistics networks has increased because of recent disasters. When we consider optimization problems, entropy regularization is a powerful tool for the div…
Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport
Kazuki Shibata, Tomohiko Jimbo, Takamitsu Matsubara
In this paper, we present a solution to a design problem of control strategies for multi-agent cooperative transport. Although existing learning-based methods assume that the numbe…
Tracking Control foe Multi-Agent Systems Using Broadcast Signals Based on Positive Realness
Yasushi Amano, Tomohiko Jimbo, Kenji Fujimoto
Broadcast control is one of decentralized control methods for networked multi-agent systems. In this method, each agent does not communicate with the others, and autonomously deter…
Development of global optimal coverage control using multiple aerial robots
Kazuki Shibata, Tatsuya Miyano, Tomohiko Jimbo
Coverage control has been widely used for constructing mobile sensor network such as for environmental monitoring, and one of the most commonly used methods is the Lloyd algorithm…
Robust shape estimation with false-positive contact detection
Kazuki Shibata, Tatsuya Miyano, Tomohiko Jimbo +1
We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contac…