23 citations · 158 across the 38 of their papers we have counts for
38 papers
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators
Abhishek Tyagi, Yiming Gan, Shaoshan Liu +3
As Deep Neural Networks (DNNs) are increasingly deployed in safety critical and privacy sensitive applications such as autonomous driving and biometric authentication, it is critic…
AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments
Tim Tianyi Yang, Tom Tianze Yang, Andrew Liu +4
Under the Autonomous Mobile Clinics (AMCs) initiative, we are developing, open sourcing, and standardizing health AI technologies to enable healthcare access in least developed cou…
INTERNEURON: A Middleware with Multi-Network Communication Reliability for Infrastructure Vehicle Cooperative Autonomous Driving
Tianze Wu, Shaoshan Liu, Bo Yu +3
Infrastructure-Vehicle Cooperative Autonomous Driving (IVCAD) is a new paradigm of autonomous driving, which relies on the cooperation between intelligent roads and autonomous vehi…
Programming Autonomous Machines
Shaoshan Liu, Xiaoming Li, Tongsheng Geng +2
One key technical challenge in the age of autonomous machines is the programming of autonomous machines, which demands the synergy across multiple domains, including fundamental co…
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System
Shaoshan Liu, Jianda Wang, Zhendong Wang +7
This paper is the first to provide a thorough system design overview along with the fusion methods selection criteria of a real-world cooperative autonomous driving system, named I…
Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities
Zishen Wan, Ashwin Lele, Bo Yu +5
Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous…
An Energy-Efficient and Runtime-Reconfigurable FPGA-Based Accelerator for Robotic Localization Systems
Qiang Liu, Zishen Wan, Bo Yu +3
Simultaneous Localization and Mapping (SLAM) estimates agents' trajectories and constructs maps, and localization is a fundamental kernel in autonomous machines at all computing sc…
Enabling Level-4 Autonomous Driving on a Single $1k Off-the-Shelf Card
Hsin-Hsuan Sung, Yuanchao Xu, Jiexiong Guan +5
Autonomous driving is of great interest in both research and industry. The high cost has been one of the major roadblocks that slow down the development and adoption of autonomous…
Dataflow Accelerator Architecture for Autonomous Machine Computing
Shaoshan Liu, Yuhao Zhu, Bo Yu +2
Commercial autonomous machines is a thriving sector, one that is likely the next ubiquitous computing platform, after Personal Computers (PC), cloud computing, and mobile computing…
4C: A Computation, Communication, and Control Co-Design Framework for CAVs
Liangkai Liu, Shaoshan Liu, Weisong Shi
Connected and autonomous vehicles (CAVs) are promising due to their potential safety and efficiency benefits and have attracted massive investment and interest from government agen…
Rise of the Autonomous Machines
Shaoshan Liu, Jean-Luc Gaudiot
After decades of uninterrupted progress and growth, information technology has so evolved that it can be said we are entering the age of autonomous machines, but there exist many r…
iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform
Tian Gao, Zishen Wan, Yuyang Zhang +4
Stereo matching is a critical task for robot navigation and autonomous vehicles, providing the depth estimation of surroundings. Among all stereo matching algorithms, Efficient Lar…
An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform
Zishen Wan, Yuyang Zhang, Arijit Raychowdhury +3
In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target. In thi…
The Matter of Time -- A General and Efficient System for Precise Sensor Synchronization in Robotic Computing
Shaoshan Liu, Bo Yu, Yahui Liu +5
Time synchronization is a critical task in robotic computing such as autonomous driving. In the past few years, as we developed advanced robotic applications, our synchronization s…
Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunities
Shaoshan Liu, Bo Yu, Jie Tang +1
The infrastructure-vehicle cooperative autonomous driving approach depends on the cooperation between intelligent roads and intelligent vehicles. This approach is not only safer bu…
Engineering Education in the Age of Autonomous Machines
Shaoshan Liu, Jean-Luc Gaudiot, Hironori Kasahara
In the past few years, we have observed a huge supply-demand gap for autonomous driving engineers. The core problem is that autonomous driving is not one single technology but rath…
Eudoxus: Characterizing and Accelerating Localization in Autonomous Machines
Yiming Gan, Bo Yu, Boyuan Tian +7
We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe. A critical challenge to our -- and any -- autonomous machine is a…
On Designing Computing Systems for Autonomous Vehicles: a PerceptIn Case Study
Bo Yu, Jie Tang, Shaoshan Liu
PerceptIn develops and commercializes autonomous vehicles for micromobility around the globe. This paper makes a holistic summary of PerceptIn's development and operating experienc…
An Energy-Efficient High Definition Map Data Distribution Mechanism for Autonomous Driving
Jinliang Xie, Jie Tang, Shaoshan Liu
Autonomous Driving is now the promising future of transportation. As one basis for autonomous driving, High Definition Map (HD map) provides high-precision descriptions of the envi…
A Survey of FPGA-Based Robotic Computing
Zishen Wan, Bo Yu, Thomas Yuang Li +5
Recent researches on robotics have shown significant improvement, spanning from algorithms, mechanics to hardware architectures. Robotics, including manipulators, legged robots, dr…
Real-Time Spatio-Temporal LiDAR Point Cloud Compression
Yu Feng, Shaoshan Liu, Yuhao Zhu
Compressing massive LiDAR point clouds in real-time is critical to autonomous machines such as drones and self-driving cars. While most of the recent prior work has focused on comp…
CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way
Shaoshan Liu, Bin Ren, Xipeng Shen +1
Assuming hardware is the major constraint for enabling real-time mobile intelligence, the industry has mainly dedicated their efforts to developing specialized hardware accelerator…
Autonomous Last-mile Delivery Vehicles in Complex Traffic Environments
Bai Li, Shaoshan Liu, Jie Tang +3
E-commerce has evolved with the digital technology revolution over the years. Last-mile logistics service contributes a significant part of the e-commerce experience. In contrast t…
Enabling Commercial Autonomous Space Robotic Explorers
Thomas Yuang Li, Shaoshan Liu
In contrast to manned missions, the application of autonomous robots for space exploration missions decreases the safety concerns of the exploration missions while extending the ex…