Vision-based robotic gras** from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …
conclude three key tasks during vision-based robotic gras**, which are object localization …
Data-driven robotic visual gras** detection for unknown objects: A problem-oriented review
H Tian, K Song, S Li, S Ma, J Xu, Y Yan - Expert Systems with Applications, 2023 - Elsevier
This paper presents a comprehensive survey of data-driven robotic visual gras**
detection (DRVGD) for unknown objects. We review both object-oriented and scene …
detection (DRVGD) for unknown objects. We review both object-oriented and scene …
End-to-end trainable deep neural network for robotic grasp detection and semantic segmentation from rgb
In this work, we introduce a novel, end-to-end trainable CNN-based architecture to deliver
high quality results for grasp detection suitable for a parallel-plate gripper, and semantic …
high quality results for grasp detection suitable for a parallel-plate gripper, and semantic …
Invigorate: Interactive visual grounding and gras** in clutter
H Zhang, Y Lu, C Yu, D Hsu, X Lan, N Zheng - ar**_of_Objects_in_Robotics/links/6525bee2c64260390bde97ef/Comprehensive-Review-on-Reaching-and-Gras**-of-Objects-in-Robotics.pdf" data-clk="hl=fr&sa=T&oi=gga&ct=gga&cd=4&d=6374463647530486634&ei=BUWnZ7CiG9qQieoPmofEoAY" data-clk-atid="aguyAOqkdlgJ" target="_blank">[PDF] researchgate.net
Comprehensive review on reaching and gras** of objects in robotics
QM Marwan, SC Chua, LC Kwek - Robotica, 2021 - cambridge.org
Interaction between a robot and its environment requires perception about the environment,
which helps the robot in making a clear decision about the object type and its location. After …
which helps the robot in making a clear decision about the object type and its location. After …
Predicting stable configurations for semantic placement of novel objects
C Paxton, C ** from classical to modern: A survey
Planning for multi-object manipulation with graph neural network relational classifiers
Objects rarely sit in isolation in human environments. As such, we'd like our robots to reason
about how multiple objects relate to one another and how those relations may change as the …
about how multiple objects relate to one another and how those relations may change as the …
A single multi-task deep neural network with post-processing for object detection with reasoning and robotic grasp detection
Applications of deep neural network (DNN) based object and grasp detections could be
expanded significantly when the network output is processed by a high-level reasoning over …
expanded significantly when the network output is processed by a high-level reasoning over …
Regrad: A large-scale relational grasp dataset for safe and object-specific robotic gras** in clutter
Despite the impressive progress achieved in robotic gras**, robots are not skilled in
sophisticated tasks (eg search and grasp a specified target in clutter). Such tasks involve not …
sophisticated tasks (eg search and grasp a specified target in clutter). Such tasks involve not …