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Found 4 papers, 0 papers with code
Real-world Instance-specific Image Goal Navigation for Service Robots: Bridging the Domain Gap with Contrastive Learning
To address this, we propose a novel method called Few-shot Cross-quality Instance-aware Adaptation (CrossIA), which employs contrastive learning with an instance classifier to align features between massive low- and few high-quality images.
Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation
This study provides insights into the technical aspects of the proposed method, including active perception and exploration by the robot, and how the method can enable mobile robots to learn spatial concepts through active exploration.
Map completion from partial observation using the global structure of multiple environmental maps
Using the spatial structure of various indoor environments as prior knowledge, the robot would construct the map more efficiently.
Autonomous Planning Based on Spatial Concepts to Tidy Up Home Environments with Service Robots
We evaluate the effectiveness of the proposed method by an experimental simulation that reproduces the conditions of the Tidy Up Here task of the World Robot Summit 2018 international robotics competition.
