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Found 15 papers, 7 papers with code
DITTO: Demonstration Imitation by Trajectory Transformation
Subsequently, in the live online trajectory generation stage, we first \mbox{re-detect} all objects, then we warp the demonstration trajectory to the current scene, and finally, we trace the trajectory with the robot.
CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimation
It consists of an RGB-D image encoder that leverages recent advances to detect objects and infer their pose and latent code, and a decoder to predict shape and grasps for each object in the scene.
Robot Skill Generalization via Keypoint Integrated Soft Actor-Critic Gaussian Mixture Models
A long-standing challenge for a robotic manipulation system operating in real-world scenarios is adapting and generalizing its acquired motor skills to unseen environments.
Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation
We present HIMOS, a hierarchical reinforcement learning approach that learns to compose exploration, navigation, and manipulation skills.
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation
We employ our method to learn challenging multi-object robot manipulation tasks from wrist camera observations and demonstrate superior utility for policy learning compared to other representation learning techniques.
Improving Deep Dynamics Models for Autonomous Vehicles with Multimodal Latent Mapping of Surfaces
By training everything end-to-end with the loss of the dynamics model, we enforce the latent mapper to learn an update rule for the latent map that is useful for the subsequent dynamics model.
Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
Early stopping based on the validation set performance is a popular approach to find the right balance between under- and overfitting in the context of supervised learning.
Model-based Reinforcement Learning
reinforcement-learning
+1
N$^2$M$^2$: Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments
Despite its importance in both industrial and service robotics, mobile manipulation remains a significant challenge as it requires a seamless integration of end-effector trajectory generation with navigation skills as well as reasoning over long-horizons.
Self-Supervised Learning of Multi-Object Keypoints for Robotic Manipulation
In recent years, policy learning methods using either reinforcement or imitation have made significant progress.
Doing Right by Not Doing Wrong in Human-Robot Collaboration
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human collaborators feel unsafe or to treat them unfairly.
Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds
Audio-visual navigation combines sight and hearing to navigate to a sound-emitting source in an unmapped environment.
Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models
A core challenge for an autonomous agent acting in the real world is to adapt its repertoire of skills to cope with its noisy perception and dynamics.
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning
Accurate value estimates are important for off-policy reinforcement learning.
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning
Our reinforcement learning agent learns a policy for a centralized controller to let connected autonomous vehicles at unsignalized intersections give up their right of way and yield to other vehicles to optimize traffic flow.
3D Human Pose Estimation in RGBD Images for Robotic Task Learning
We propose an approach to estimate 3D human pose in real world units from a single RGBD image and show that it exceeds performance of monocular 3D pose estimation approaches from color as well as pose estimation exclusively from depth.
Ranked #14 on
3D Human Pose Estimation
on Total Capture
