Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Hsiao, Yu-Shun"'
Autor:
Hsiao, Yu-Shun, Hari, Siva Kumar Sastry, Sundaralingam, Balakumar, Yik, Jason, Tambe, Thierry, Sakr, Charbel, Keckler, Stephen W., Reddi, Vijay Janapa
High-dimensional motion generation requires numerical precision for smooth, collision-free solutions. Typically, double-precision or single-precision floating-point (FP) formats are utilized. Using these for big tensors imposes a strain on the memory
Externí odkaz:
http://arxiv.org/abs/2310.07854
Autor:
Mayoral-Vilches, Víctor, Jabbour, Jason, Hsiao, Yu-Shun, Wan, Zishen, Crespo-Álvarez, Martiño, Stewart, Matthew, Reina-Muñoz, Juan Manuel, Nagras, Prateek, Vikhe, Gaurav, Bakhshalipour, Mohammad, Pinzger, Martin, Rass, Stefan, Panigrahi, Smruti, Corradi, Giulio, Roy, Niladri, Gibbons, Phillip B., Neuman, Sabrina M., Plancher, Brian, Reddi, Vijay Janapa
We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its common baseline. The suite encompasses ROS 2 packages covering the full r
Externí odkaz:
http://arxiv.org/abs/2309.09212
Autor:
Hsiao, Yu-Shun, Hari, Siva Kumar Sastry, Filipiuk, Michał, Tsai, Timothy, Sullivan, Michael B., Reddi, Vijay Janapa, Singh, Vasu, Keckler, Stephen W.
The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort. This paper proposes a sensor frame processing rate (F
Externí odkaz:
http://arxiv.org/abs/2205.03347
Autor:
Jia, Tianyu, Yang, En-Yu, Hsiao, Yu-Shun, Cruz, Jonathan, Brooks, David, Wei, Gu-Yeon, Reddi, Vijay Janapa
Autonomous machines (e.g., vehicles, mobile robots, drones) require sophisticated 3D mapping to perceive the dynamic environment. However, maintaining a real-time 3D map is expensive both in terms of compute and memory requirements, especially for re
Externí odkaz:
http://arxiv.org/abs/2205.03325
Autor:
Wan, Zishen, Anwar, Aqeel, Mahmoud, Abdulrahman, Jia, Tianyu, Hsiao, Yu-Shun, Reddi, Vijay Janapa, Raychowdhury, Arijit
Swarm intelligence is being increasingly deployed in autonomous systems, such as drones and unmanned vehicles. Federated reinforcement learning (FRL), a key swarm intelligence paradigm where agents interact with their own environments and cooperative
Externí odkaz:
http://arxiv.org/abs/2203.07276
Autor:
Wan, Zishen, Anwar, Aqeel, Hsiao, Yu-Shun, Jia, Tianyu, Reddi, Vijay Janapa, Raychowdhury, Arijit
Learning-based navigation systems are widely used in autonomous applications, such as robotics, unmanned vehicles and drones. Specialized hardware accelerators have been proposed for high-performance and energy-efficiency for such navigational tasks.
Externí odkaz:
http://arxiv.org/abs/2111.04957
Autor:
Hsiao, Yu-Shun, Wan, Zishen, Jia, Tianyu, Ghosal, Radhika, Mahmoud, Abdulrahman, Raychowdhury, Arijit, Brooks, David, Wei, Gu-Yeon, Reddi, Vijay Janapa
Safety and resilience are critical for autonomous unmanned aerial vehicles (UAVs). We introduce MAVFI, the micro aerial vehicles (MAVs) resilience analysis methodology to assess the effect of silent data corruption (SDC) on UAVs' mission metrics, suc
Externí odkaz:
http://arxiv.org/abs/2105.12882
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