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Found 8 papers, 1 papers with code
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
In each iteration, the image is annotated with a visual representation of proposals that the VLM can refer to (e. g., candidate robot actions, localizations, or trajectories).
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Our goal is to enable a single end-to-end trained model to both learn to map robot observations to actions and enjoy the benefits of large-scale pretraining on language and vision-language data from the web.
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation.
Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous
We propose hierarchical predictive planning (HPP), a model-based reinforcement learning method for decentralized multiagent rendezvous.
Model-based Reinforcement Learning
reinforcement-learning
+1
Neural Collision Clearance Estimator for Batched Motion Planning
We present a neural network collision checking heuristic, ClearanceNet, and a planning algorithm, CN-RRT.
Learned Critical Probabilistic Roadmaps for Robotic Motion Planning
Critical PRMs are demonstrated to achieve up to three orders of magnitude improvement over uniform sampling, while preserving the guarantees and complexity of sampling-based motion planning.
Long Range Neural Navigation Policies for the Real World
Learned Neural Network based policies have shown promising results for robot navigation.
Long-Range Indoor Navigation with PRM-RL
Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings.
