MIF integrates appearance, spatial, and geometry fields with discrepancy detection to raise humanoid relocation success from 12% to 94% in dynamic offices while cutting memory use by 91.4%.
Learning to reason over scene graphs: a case study of finetuning gpt-2 into a robot language model for grounded task planning.Frontiers in Robotics and AI, 10:1221739
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Learning to Evolve: Multi-modal Interactive Fields for Robust Humanoid Navigation in Dynamic Environments
MIF integrates appearance, spatial, and geometry fields with discrepancy detection to raise humanoid relocation success from 12% to 94% in dynamic offices while cutting memory use by 91.4%.