activity
20182023
most citedPoint-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

102 citations · 113 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SY2023★ 1 cited

Assigning Optimal Integer Harmonic Periods to Hard Real Time Tasks

Anand Bhat, Ragunathan Rajkumar

Selecting period values for tasks is a very important step in the design process of a real-time system, especially due to the significance of its impact on system schedulability. I…

cs.MA2022

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Shunsuke Aoki, Ragunathan, Rajkumar

Connected and Automated Vehicles (CAVs) are highly expected to improve traffic throughput and safety at road intersections, single-track lanes, and construction zones. However, mul…

cs.RO2021★ 3 cited

MultiCruise: Eco-Lane Selection Strategy with Eco-Cruise Control for Connected and Automated Vehicles

Shunsuke Aoki, Lung En Jan, Junfeng Zhao +4

Connected and Automated Vehicles (CAVs) have real-time information from the surrounding environment by using local on-board sensors, V2X (Vehicle-to-Everything) communications, pre…

cs.CV2020★ 1 cited

CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion

Iljoo Baek, Tzu-Chieh Tai, Manoj Bhat +5

Reliable curb detection is critical for safe autonomous driving in urban contexts. Curb detection and tracking are also useful in vehicle localization and path planning. Past work…

eess.SY2020

Co-simulation Platform for Developing InfoRich Energy-Efficient Connected and Automated Vehicles

Shunsuke Aoki, Lung En Jan, Junfeng Zhao +4

With advances in sensing, computing, and communication technologies, Connected and Automated Vehicles (CAVs) are becoming feasible. The advent of CAVs presents new opportunities to…

cs.CV2020★ 102 cited

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

Weijing Shi, Ragunathan, Rajkumar

In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbor…