#robot-learning
Research tagged robot-learning: explanations, evidence, limitations and connections between papers.
9 results
GLIO2 completes a route with weak LiDAR geometry
GLIO2 jointly updates LiDAR, inertial, and satellite measurements, completing a tested degenerate bridge route where LiDAR systems diverged.
Human motion helps humanoid robots follow instructions
VioLA uses shared human and robot motion targets to train humanoid control, with strong results in one laboratory evaluation.
Rewarding diverse robot successes improved tested shift averages
DRIVE rewards diverse successful robot behavior; simulation and two physical tasks show higher average success under tested shifts.
Juno connects robot predictions to motion and action learning
Juno links motion-aware robot predictions to action learning, with gains in tested simulation tasks and physical shifts.
Robot history helps most when video learning predicts forward
Robot tests find longer visual history helps after causal video pretraining, while bidirectional pretraining shows no net gain.
RealtimeWAM speeds robot action prediction while keeping success
RealtimeWAM coordinates computation in robot action models, lowering average simulation latency while keeping task success close to original inference.
Rules help frozen robot models handle new wording
A rule-based rewriter improved a frozen robot model on new instruction phrasings in simulated tasks.
TouchScale pairs 500 hours of human video with touch
A 500-hour visual-and-touch dataset improves contact prediction and robot task success in the tested settings.
Robot models learn from executed action alternatives to predict failures
CureWM repairs released robot world models with executed action alternatives, improving success–failure prediction in several tested settings.