Rise of the Autonomous Machines
Not on the map. Why?
Abstract (arXiv)
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 roadblocks in the way of making this a reality. In this article, we make a preliminary attempt at recognizing and categorizing the technical and non-technical challenges of autonomous machines; for each of the ten areas we have identified, we review current status, roadblocks, and potential research directions. It is hoped that this will help the community define clear, effective, and more formal development goalposts for the future.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 20 references that are in the map. First posted on arXiv 26 Jun 2021.
Builds on
8 of 20 references.
References · 8
- 2020Deep Reinforcement Learning for Autonomous Driving: A Surveycited by 698
- 2021The Matter of Time -- A General and Efficient System for Precise Sensor Synchronization in Robotic Computingcited by 6
- 2020Eudoxus: Characterizing and Accelerating Localization in Autonomous Machinescited by 5
- 2018Teaching Autonomous Driving Using a Modular and Integrated Approachcited by 3
- 2020Autonomous Last-mile Delivery Vehicles in Complex Traffic Environmentscited by 2
- 2021Engineering Education in the Age of Autonomous Machinescited by 2
- 2021iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platformcited by 2
- 2021Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunitiescited by 1
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
3 papers.