A survey of imitation learning: Algorithms, recent developments, and challenges

M Zare, PM Kebria, A Khosravi… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In recent years, the development of robotics and artificial intelligence (AI) systems has been
nothing short of remarkable. As these systems continue to evolve, they are being utilized in …

Offline imitation learning through graph search and retrieval

ZH Yin, P Abbeel - arxiv preprint arxiv:2407.15403, 2024 - arxiv.org
Imitation learning is a powerful machine learning algorithm for a robot to acquire
manipulation skills. Nevertheless, many real-world manipulation tasks involve precise and …

Cloud-Based Hierarchical Imitation Learning for Scalable Transfer of Construction Skills from Human Workers to Assisting Robots

H Yu, VR Kamat, CC Menassa - Journal of Computing in Civil …, 2024 - ascelibrary.org
Assigning repetitive and physically demanding construction tasks to robots can alleviate
human workers' exposure to occupational injuries, which often result in significant downtime …

Towards Effective Utilization of Mixed-Quality Demonstrations in Robotic Manipulation via Segment-Level Selection and Optimization

J Chen, H Fang, HS Fang, C Lu - arxiv preprint arxiv:2409.19917, 2024 - arxiv.org
Data is crucial for robotic manipulation, as it underpins the development of robotic systems
for complex tasks. While high-quality, diverse datasets enhance the performance and …

Inverse Reinforcement Learning by Estimating Expertise of Demonstrators

M Beliaev, R Pedarsani - arxiv preprint arxiv:2402.01886, 2024 - arxiv.org
In Imitation Learning (IL), utilizing suboptimal and heterogeneous demonstrations presents a
substantial challenge due to the varied nature of real-world data. However, standard IL …

Multi-stage multi-modal pre-training for automatic speech recognition

Y Jain, D Chan, P Dheram, A Khare… - arxiv preprint arxiv …, 2024 - arxiv.org
Recent advances in machine learning have demonstrated that multi-modal pre-training can
improve automatic speech recognition (ASR) performance compared to randomly initialized …