iSDF: Real-Time Neural Signed Distance Fields for Robot Perception

摘要

Online optimisation / continual learning Latest frame (RGB unused) Fig. To train the network in real-time we develop a batch-based self-supervision method. This network can be queried online to obtain collision costs and gradients for use by downstream planners in domains from navigation to manipulation. The trajectory (red) of the camera (green) is visualised on top of the zero level set (top row) and SDF slice (middle row) generated by iSDF over time (left to right).