End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
Parallel manufacturing for industrial metaverses: A new paradigm in smart manufacturing
J Yang, X Wang, Y Zhao - IEEE/CAA Journal of Automatica …, 2022 - ieeexplore.ieee.org
Briefing: To tackle the complexity of human and social factors in manufacturing systems,
parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart …
parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart …
A framework and operational procedures for metaverses-based industrial foundation models
Industrial processes are typical cyber–physical–social systems (CPSSs), where the effective
management of employees and the efficient control of machines play important roles …
management of employees and the efficient control of machines play important roles …
DeFACT in ManuVerse for parallel manufacturing: Foundation models and parallel workers in smart factories
In cyber–physical–social systems, smart manufacturing has to overcome challenges, such
as uncertainty, diversity, complexity in modeling, long-delayed responses to market …
as uncertainty, diversity, complexity in modeling, long-delayed responses to market …
Vision-based autonomous car racing using deep imitative reinforcement learning
Autonomous car racing is a challenging task in the robotic control area. Traditional modular
methods require accurate mapping, localization and planning, which makes them …
methods require accurate mapping, localization and planning, which makes them …
Software-defined active LiDARs for autonomous driving: A parallel intelligence-based adaptive model
LiDAR is an indispensable sensor for autonomous driving that can provide precise 3D
information about the environment. Among various types of LiDARs, mechanical LiDARs are …
information about the environment. Among various types of LiDARs, mechanical LiDARs are …
A parallel teacher for synthetic-to-real domain adaptation of traffic object detection
Large-scale synthetic traffic image datasets have been widely used to make compensate for
the insufficient data in real world. However, the mismatch in domain distribution between …
the insufficient data in real world. However, the mismatch in domain distribution between …
Probabilistic end-to-end vehicle navigation in complex dynamic environments with multimodal sensor fusion
All-day and all-weather navigation is a critical capability for autonomous driving, which
requires proper reaction to varied environmental conditions and complex agent behaviors …
requires proper reaction to varied environmental conditions and complex agent behaviors …
Learning from interaction-enhanced scene graph for pedestrian collision risk assessment
X Liu, Y Zhou, C Gou - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Collision risk assessment aims to provide a subjective cognitive comprehension of the risk
level in driving scenarios, which is critical for the safety of autonomous driving systems …
level in driving scenarios, which is critical for the safety of autonomous driving systems …
DQ-GAT: Towards safe and efficient autonomous driving with deep Q-learning and graph attention networks
Autonomous driving in multi-agent dynamic traffic scenarios is challenging: the behaviors of
road users are uncertain and are hard to model explicitly, and the ego-vehicle should apply …
road users are uncertain and are hard to model explicitly, and the ego-vehicle should apply …