Agents of Autonomy: A Systematic Study of Robotics on Modern Hardware
Pages 25 - 26
Abstract
As robots increasingly permeate modern society, it is crucial for the system and hardware research community to bridge its long-standing gap with robotics. This divide has persisted due to the lack of (i) a systematic performance evaluation of robotics on different computing platforms and (ii) a comprehensive, open-source, cross-platform benchmark suite.
To address these gaps, we present a systematic performance study of robotics on modern hardware and introduce RoWild, an open-source benchmark suite for robotics that is comprehensive and cross-platform. Our workloads encompass a broad range of robots, including driverless vehicles, pilotless drones, and stationary robotic arms, and we evaluate their performance on a spectrum of modern computing platforms, from low-end embedded CPUs to high-end server-grade GPUs.
Our findings reveal that current architectures experience significant inefficiencies when executing robotic workloads, highlighting the need for architectural advancements. We discuss approaches for meeting these requirements, offering insights for improving the performance of robotics.
The full version of the paper is available in [11], and the source code of the benchmark suite is available in [2].
References
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2023. RoWild: A Comprehensive, Cross-Platform Benchmark Suite for Real-Time Robotics. https://cmu-roboarch.github.io/rowild/.
[3]
n.d. CppRobotics. https://github.com/onlytailei/CppRobotics/.
[4]
n.d. Freiburg Campus 360 Degree 3D Scans. http://ais.informatik.uni-freiburg.de/ projects/datasets/fr360/.
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n.d. Intel Research Lab. http://www2.informatik.uni-freiburg.de/%7Estachnis/ datasets/datasets/intel-lab/intel.gfs.png.
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n.d. PythonRobotics. https://github.com/AtsushiSakai/PythonRobotics/.
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n.d. ROS - Robot Operating System. https://www.ros.org/.
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Mohammad Bakhshalipour et al. 2022b. RTRBench: A Benchmark Suite for Real-Time Robotics. In ISPASS. https://cmu-roboarch.github.io/rtrbench/.
[11]
Mohammad Bakhshalipour and Phillip B. Gibbons. 2023. Agents of Autonomy: A Systematic Study of Robotics on Modern Hardware. Proc. ACM Meas. Anal. Comput. Syst. (2023).
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Behzad Boroujerdian et al. 2018. MAVBench: Micro Aerial Vehicle Benchmarking. In MICRO.
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Mihai Bujanca et al. 2019. SLAMBench 3.0: Systematic Automated Reproducible Evaluation of SLAM Systems for Robot Vision Challenges and Scene Understanding. In ICRA.
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Chieh Chung and Chia-Hsiang Yang. 2019. A Distributed Autonomous and Collaborative Multi-Robot System Featuring a Low-Power Robot SoC in 22nm CMOS for Integrated Battery-Powered Minibots. In ISSCC.
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Chieh Chung and Chia-Hsiang Yang. 2020. A 1.5-μJ/Task Path-Planning Processor for 2-D/3-D Autonomous Navigation of Microrobots. JSSC (2020).
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Stephen James et al. 2020. RLBench: The Robot Learning Benchmark & Learning Environment. IEEE Robotics and Automation Letters (2020).
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Youchang Kim et al. 2016. A 0.55V 1.1mW Artificial-Intelligence Processor with PVT Compensation for Micro Robots. In ISSCC.
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Weizhuang Liu et al. 2021. Archytas: A Framework for Synthesizing and Dynamically Optimizing Accelerators for Robotic Localization. In MICRO.
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Jacob Sacks et al. 2018. RoboX: An End-To-End Solution to Accelerate Autonomous Control in Robotics. In ISCA.
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Bo Yu et al. 2020. Building the Computing System for Autonomous Micromobility Vehicles: Design Constraints and Architectural Optimizations. In MICRO.
Index Terms
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Published In
June 2024
120 pages
ISBN:9798400706240
DOI:10.1145/3652963
- General Chairs:
- Michele Garetto,
- Andrea Marin,
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- Florin Ciucu,
- Giulia Fanti,
- Rhonda Righter
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Published: 10 June 2024
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