Combining navigation and manipulation costs for time-efficient robot placement in mobile manipulation tasks
Mobile manipulation tasks require a seamless integration of navigation and manipulation
capabilities. Finding suitable robot placements to pick up and place objects in such tasks is …
capabilities. Finding suitable robot placements to pick up and place objects in such tasks is …
Review of reinforcement learning for robotic grasping: Analysis and recommendations
This review paper provides a comprehensive analysis of over 100 research papers focused
on the challenges of robotic grasping and the effectiveness of various machine learning …
on the challenges of robotic grasping and the effectiveness of various machine learning …
Learning to Grasp on the Moon from 3D Octree Observations with Deep Reinforcement Learning
Extraterrestrial rovers with a general-purpose robotic arm have many potential applications
in lunar and planetary exploration. Introducing autonomy into such systems is desirable for …
in lunar and planetary exploration. Introducing autonomy into such systems is desirable for …
Push-to-see: learning non-prehensile manipulation to enhance instance segmentation via deep q-learning
Efficient robotic manipulation of objects for sorting and searching often rely upon how well
the objects are perceived and the available grasp poses. The challenge arises when the …
the objects are perceived and the available grasp poses. The challenge arises when the …
Learning symbolic failure detection for grasping and mobile manipulation tasks
P Hegemann, T Zechmeister, M Grotz… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
The ability to detect failure during task execution and to recover from failure is vital for
autonomous robots performing tasks in previously unknown environments. In this paper, we …
autonomous robots performing tasks in previously unknown environments. In this paper, we …
Robotic Grasping Based on Deep Learning: A Survey
MA Rashed, RN Farhan… - 2023 Second International …, 2023 - ieeexplore.ieee.org
The progress achieved in the robotics field in the last decade made the deployment of robots
possible in real-world. One of the essential skills required to do these tasks is object …
possible in real-world. One of the essential skills required to do these tasks is object …
Memory-centered and Affordance-based Framework for Mobile Manipulation
Performing versatile mobile manipulation actions in human-centered environments requires
highly sophisticated software frameworks that are flexible enough to handle special use …
highly sophisticated software frameworks that are flexible enough to handle special use …
Probabilistic spatio-temporal fusion of affordances for grasping and manipulation
Robust vision-based grasping and manipulation of unknown objects in unstructured scenes
requires the extraction of action candidates based on visual information while taking into …
requires the extraction of action candidates based on visual information while taking into …
[PDF][PDF] MAkE-able: Memory-centered and Affordance-based Task Execution Framework for Transferable Mobile Manipulation Skills
C Pohl, F Reister, F Peller-Konrad… - arXiv preprint arXiv …, 2024 - h2t.iar.kit.edu
To perform versatile mobile manipulation tasks in human-centered environments, the ability
to efficiently transfer learned tasks and experiences from one robot to another or across …
to efficiently transfer learned tasks and experiences from one robot to another or across …
Speeding up 6-DoF Grasp Sampling with Quality-Diversity
J Huber, F Hélénon, M Kappel, E Chelly… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advances in AI have led to significant results in robotic learning, including natural
language-conditioned planning and efficient optimization of controllers using generative …
language-conditioned planning and efficient optimization of controllers using generative …