Towards proactive human–robot collaboration: A foreseeable cognitive manufacturing paradigm
Human–robot collaboration (HRC) has attracted strong interests from researchers and
engineers for improved operational flexibility and efficiency towards mass personalization …
engineers for improved operational flexibility and efficiency towards mass personalization …
Develo** a deep Q-learning and neural network framework for trajectory planning
VSR Kosuru, AK Venkitaraman - European Journal of Engineering and …, 2022 - ej-eng.org
Autonomy field, every vehicle is occupied with some kind or alter driver assist features in
order to compensate driver comfort. Expansion further to fully Autonomy is extremely …
order to compensate driver comfort. Expansion further to fully Autonomy is extremely …
Motioncnn: A strong baseline for motion prediction in autonomous driving
S Konev, K Brodt, A Sanakoyeu - ar** rapidly and nowadays first autonomous rides
are being provided in city areas. This requires the highest standards for the safety and …
are being provided in city areas. This requires the highest standards for the safety and …
A scale-invariant trajectory simplification method for efficient data collection in videos
Training data is a critical requirement for machine learning tasks, and labeled training data
can be expensive to acquire, often requiring manual or semi-automated data collection …
can be expensive to acquire, often requiring manual or semi-automated data collection …
RISAT: real-time instance segmentation with adversarial training
With the development of artificial intelligence, autonomous driving has gradually attracted
attentions from academia and industry. Detecting road conditions correctly and timely is …
attentions from academia and industry. Detecting road conditions correctly and timely is …
BoT-Drive: Hierarchical Behavior and Trajectory Planning for Autonomous Driving using POMDPs
X **, C Zeng, S Zhu, C Liu, P Cai - arxiv preprint arxiv:2409.18411, 2024 - arxiv.org
Uncertainties in dynamic road environments pose significant challenges for behavior and
trajectory planning in autonomous driving. This paper introduces BoT-Drive, a planning …
trajectory planning in autonomous driving. This paper introduces BoT-Drive, a planning …
NeuroSMPC: A Neural Network Guided Sampling Based MPC for On-Road Autonomous Driving
In this paper we show an effective means of integrating data driven frameworks to sampling
based optimal control to vastly reduce the compute time for easy adoption and adaptation to …
based optimal control to vastly reduce the compute time for easy adoption and adaptation to …