Introduces an incremental reachable graph and structural priors for multi-floor ground robot exploration, showing improved efficiency in simulation and real-time onboard performance.
Elevation mapping for locomotion and navigation using gpu
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.
citing papers explorer
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Multi-Floor Exploration for Ground Robots via an Incremental Reachable Graph and Structural Priors
Introduces an incremental reachable graph and structural priors for multi-floor ground robot exploration, showing improved efficiency in simulation and real-time onboard performance.
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Learning Locomotion on Complex Terrain for Quadrupedal Robots with Foot Position Maps and Stability Rewards
Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.