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Daigo Shishika

13 accepted papers

2024

Bi-CL: A Reinforcement Learning Framework for Robots Coordination Through Bi-level Optimization

IROS 2024poster

In multi-robot systems, achieving coordinated missions remains a significant challenge due to the coupled nature of coordination behaviors and the lack of global information for individual robots. To mitigate these challenges, this paper introduces a novel approach, Bi-level Coordination Learning (B…

Cited by 3SourceScholar
2024

Learning Coordinated Maneuver in Adversarial Environments

IROS 2024poster

This paper aims to solve the coordination of a team of robots traversing a route in the presence of adversaries with random positions. Our goal is to minimize the overall cost of the team, which is determined by (i) the accumulated risk when robots stay in adversary-impacted zones and (ii) the missi…

Cited by 0SourceScholar
2024

Scaling Team Coordination on Graphs with Reinforcement Learning

ICRA 2024poster

This paper studies Reinforcement Learning (RL) techniques to enable team coordination behaviors in graph environments with support actions among teammates to reduce the costs of traversing certain risky edges in a centralized manner. While classical approaches can solve this non-standard multi-agent…

Cited by 6SourceScholar
2024

Team Coordination on Graphs: Problem, Analysis, and Algorithms

IROS 2024poster

Team Coordination on Graphs with Risky Edges (TCGRE) is a recently emerged problem, in which a robot team collectively reduces graph traversal cost through support from one robot to another when the latter traverses a risky edge. Resembling the traditional Multi-Agent Path Finding (MAPF) problem, bo…

Cited by 3SourceScholar
2023

Team Coordination on Graphs with State-Dependent Edge Costs

IROS 2023poster

This paper studies a team coordination problem in a graph environment. Specifically, we incorporate “support” action which an agent can take to reduce the cost for its teammate to traverse some high cost edges. Due to this added feature, the graph traversal is no longer a standard multi-agent path p…

Cited by 9SourceScholar
2020

Adaptive Partitioning for Coordinated Multi-agent Perimeter Defense

IROS 2020poster

Multi-Robot Systems have been recently employed in different applications and have advantages over single-robot systems, such as increased robustness and task performance efficiency. We consider such assemblies specifically in the scenario of perimeter defense, where the task is to defend a circular…

Cited by 32SourceScholar
2020

DC-CAPT: Concurrent Assignment and Planning of Trajectories for Dubins Cars

ICRA 2020poster

We present an algorithm for the concurrent assignment and planning of collision-free trajectories (DC-CAPT) for robots whose kinematics can be modeled as Dubins cars, i.e., robots constrained in terms of their initial orientation and their minimum turning radius. Coupling the assignment and trajecto…

Cited by 3SourceScholar
2020

Game Theoretic Formation Design for Probabilistic Barrier Coverage

IROS 2020poster

We study strategies to deploy defenders/sensors to detect intruders that approach a targeted region. This scenario is formulated as a barrier coverage, which aims to minimize the number of unseen paths. The problem becomes challenging when the number of defenders is insufficient for a full coverage,…

Cited by 7SourceScholar
2019

Decentralization of Multiagent Policies by Learning What to Communicate

ICRA 2019poster

Effective communication is required for teams of robots to solve sophisticated collaborative tasks. In practice it is typical for both the encoding and semantics of communication to be manually defined by an expert; this is true regardless of whether the behaviors themselves are bespoke, optimizatio…

Cited by 36SourceScholar