A survey on deep learning and deep reinforcement learning in robotics with a tutorial on deep reinforcement learning
This article is about deep learning (DL) and deep reinforcement learning (DRL) works
applied to robotics. Both tools have been shown to be successful in delivering data-driven …
applied to robotics. Both tools have been shown to be successful in delivering data-driven …
Reducing collision checking for sampling-based motion planning using graph neural networks
Sampling-based motion planning is a popular approach in robotics for finding paths in
continuous configuration spaces. Checking collision with obstacles is the major …
continuous configuration spaces. Checking collision with obstacles is the major …
Goal distance-based UAV path planning approach, path optimization and learning-based path estimation: GDRRT*, PSO-GDRRT* and BiLSTM-PSO-GDRRT
The basic conditions for mobile robots to be autonomous are that the mobile robot localizes
itself in the environment and knows the geometric structure of the environment (map). After …
itself in the environment and knows the geometric structure of the environment (map). After …
Nerp: Neural rearrangement planning for unknown objects
AH Qureshi, A Mousavian, C Paxton, MC Yip… - ar** for suture needles using reinforcement learning for rapid motion planning
Regras** a suture needle is an important yet time-consuming process in suturing. To
bring efficiency into regras**, prior work either designs a task-specific mechanism or …
bring efficiency into regras**, prior work either designs a task-specific mechanism or …