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Found 15 papers, 2 papers with code
MResT: Multi-Resolution Sensing for Real-Time Control with Vision-Language Models
Leveraging sensing modalities across diverse spatial and temporal resolutions can improve performance of robotic manipulation tasks.
Estimating Material Properties of Interacting Objects Using Sum-GP-UCB
Robots need to estimate the material and dynamic properties of objects from observations in order to simulate them accurately.
Efficient Recovery Learning using Model Predictive Meta-Reasoning
We use our approach to learn recovery skills for door-opening and evaluate them both in simulation and on a real robot with little fine-tuning.
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Questions in causality, control, and reinforcement learning go beyond the classical machine learning task of prediction under i. i. d.
Model-based Reinforcement Learning
reinforcement-learning
+1
Learning Reactive and Predictive Differentiable Controllers for Switching Linear Dynamical Models
We learn a switching linear dynamical model with contacts encoded in switching conditions as a close approximation of our system dynamics.
Generalizing Object-Centric Task-Axes Controllers using Keypoints
We empirically evaluate our approach on multiple different manipulation tasks and show its ability to generalize to large variance in object size, shape and geometry.
Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation
Manipulation tasks can often be decomposed into multiple subtasks performed in parallel, e. g., sliding an object to a goal pose while maintaining contact with a table.
Towards Robotic Assembly by Predicting Robust, Precise and Task-oriented Grasps
Robust task-oriented grasp planning is vital for autonomous robotic precision assembly tasks.
Multi-modal Transfer Learning for Grasping Transparent and Specular Objects
State-of-the-art object grasping methods rely on depth sensing to plan robust grasps, but commercially available depth sensors fail to detect transparent and specular objects.
Robotics
Camera-to-Robot Pose Estimation from a Single Image
We show experimental results for three different camera sensors, demonstrating that our approach is able to achieve accuracy with a single frame that is better than that of classic off-line hand-eye calibration using multiple frames.
Robotics
Leveraging Multimodal Haptic Sensory Data for Robust Cutting
In this paper, we propose using vibrations and force-torque feedback from the interactions to adapt the slicing motions and monitor for contact events.
Towards Precise Robotic Grasping by Probabilistic Post-grasp Displacement Estimation
Precise robotic grasping is important for many industrial applications, such as assembly and palletizing, where the location of the object needs to be controlled and known.
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
A key challenge in intelligent robotics is creating robots that are capable of directly interacting with the world around them to achieve their goals.
Robotics
