Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce SE3-Nets, which are deep networks designed to model rigid body motion from raw point cloud data. Based only on pairs of depth images along with an action vector and point wise data associations, SE3-Nets learn to segment effected object parts and predict their motion resulting from the applied force. Rather than learning point wise flow vectors, SE3-Nets predict SE3 transformations for different parts of the scene. Using simulated depth data of a table top scene and a robot manipulator,  show that the structure underlying SE3-Nets enables them to generate a far more consistent prediction of object motion than traditional flow based networks.
['Arunkumar Byravan', 'Dieter Fox']
I am writing a research paper on a idea SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks
[{"from": "human", "value": "I am writing a research paper on a idea SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce SE3-Nets, which are deep networks designed to model rigid body motion from raw point cloud data. Based only on pairs of depth images along with an action vector and point wise data associations, SE3-Nets learn to segment effected object parts and predict their motion resulting from the applied force. Rather than learning point wise flow vectors, SE3-Nets predict SE3 transformations for different parts of the scene. Using simulated depth data of a table top scene and a robot manipulator,  show that the structure underlying SE3-Nets enables them to generate a far more consistent prediction of object motion than traditional flow based networks."}]