most cited3D Point Cloud Object Detection on Edge Devices for Split Computing

6 citations · 14 across the 8 of their papers we have counts for

collaborators

11 papers

cs.SE2026

Model-Based Retargeting to Many-Core CPS: Simulink-to-OpenCL Workflow

Ryuga Chiba, Hiroshi Fujimoto, Takuya Azumi

This paper addresses the software portability gap between Model-Based Development (MBD) and advanced many-core execution for Cyber-Physical Systems (CPS). We present a workflow-pre…

cs.RO2026

Sim-to-Real Aware End-to-End Learning Environment for Micromobility

Shouma Amano, Takuya Azumi

While end-to-end autonomous driving systems show promise, their application to micromobility vehicles is hindered by simulators failing to capture specific kinematics, such as diff…

cs.SE2026

BA-TRACE: Boundary-Aware Trace Reconstruction for Scenario-Based Evaluation of Mixed AUTOSAR Adaptive and ROS 2 Vehicular Embedded Systems

Shunsuke Ito, Ryudai Iwakami, Hiroyuki Hanyu +2

Modern vehicular embedded systems increasingly combine ROS 2-based autonomous-driving stacks with AUTOSAR Adaptive Platform (AUTOSAR AP). Such mixed stacks make scenario-based eval…

cs.RO2026

VAST: V2X/Dynamic Map-Aware Autonomous Driving Systems Validation Toolchain

Shunsuke Ito, Takuya Azumi

Cooperative autonomous driving in the IoT-to-Edge-to-Cloud continuum requires system-level validation across vehicles, infrastructure sensors, edge-side Dynamic Map services, and i…

cs.DC2026

SC-MII: Infrastructure LiDAR-based 3D Object Detection on Edge Devices for Split Computing with Multiple Intermediate Outputs Integration

Taisuke Noguchi, Takayuki Nishio, Takuya Azumi

3D object detection using LiDAR-based point cloud data and deep neural networks is essential in autonomous driving technology. However, deploying state-of-the-art models on edge de…

cs.SE2025★ 2 cited

Parallelized Code Generation from Simulink Models for Event-driven and Timer-driven ROS 2 Nodes

Kenshin Obi, Ryo Yoshinaka, Hiroshi Fujimoto +1

In recent years, the complexity and scale of embedded systems, especially in the rapidly developing field of autonomous driving systems, have increased significantly. This has led…

cs.SE2025★ 1 cited

Model-based Development for Autonomous Driving Software Considering Parallelization

Kenshin Obi, Takumi Onozawa, Hiroshi Fujimoto +1

In recent years, autonomous vehicles have attracted attention as one of the solutions to various social problems. However, autonomous driving software requires real-time performanc…

cs.RO2025

D-AWSIM: Distributed Autonomous Driving Simulator for Dynamic Map Generation Framework

Shunsuke Ito, Chaoran Zhao, Ryo Okamura +1

Autonomous driving systems have achieved significant advances, and full autonomy within defined operational design domains near practical deployment. Expanding these domains requir…

cs.RO2025★ 3 cited

AUTOSAR AP and ROS 2 Collaboration Framework

Ryudai Iwakami, Bo Peng, Hiroyuki Hanyu +2

The field of autonomous vehicle research is advancing rapidly, necessitating platforms that meet real-time performance, safety, and security requirements for practical deployment.…

cs.DC2025★ 6 cited

3D Point Cloud Object Detection on Edge Devices for Split Computing

Taisuke Noguchi, Takuya Azumi

The field of autonomous driving technology is rapidly advancing, with deep learning being a key component. Particularly in the field of sensing, 3D point cloud data collected by Li…

eess.SY2025★ 2 cited

Partitioned Scheduling for DAG Tasks Considering Probabilistic Execution Time

Fuma Omori, Atsushi Yano, Takuya Azumi

Autonomous driving systems, critical for safety, require real-time guarantees and can be modeled as DAGs. Their acceleration features, such as caches and pipelining, often result i…