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Found 7 papers, 2 papers with code
Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge
In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of objects across diverse environments.
UniTeam: Open Vocabulary Mobile Manipulation Challenge
This report introduces our UniTeam agent - an improved baseline for the "HomeRobot: Open Vocabulary Mobile Manipulation" challenge.
Language-Conditioned Semantic Search-Based Policy for Robotic Manipulation Tasks
Reinforcement learning and Imitation Learning approaches utilize policy learning strategies that are difficult to generalize well with just a few examples of a task.
TIAGo RL: Simulated Reinforcement Learning Environments with Tactile Data for Mobile Robots
Tactile information is important for robust performance in robotic tasks that involve physical interaction, such as object manipulation.
Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot
The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks.
Tensor-variate Mixture of Experts for Proportional Myographic Control of a Robotic Hand
The proposed formulation takes into account the underlying structure of the data and remains efficient when few training data are available.
