TRIP builds dense 2.5D terrain maps for quadruped robots while predicting collision, inclination, and steppability risks and rejecting dynamic-object outliers.
Gait and trajectory optimization for legged systems through phase-based end- effector parameterization,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
TRIP: Terrain Traversability Mapping With Risk-Aware Prediction for Enhanced Online Quadrupedal Robot Navigation
TRIP builds dense 2.5D terrain maps for quadruped robots while predicting collision, inclination, and steppability risks and rejecting dynamic-object outliers.