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Interpreting Contact Interactions to Overcome Failure in Robot Assembly Tasks
A key challenge towards the goal of multi-part assembly tasks is finding...
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How to Train Your Differentiable Filter
In many robotic applications, it is crucial to maintain a belief about t...
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Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving
Multi-object tracking is an important ability for an autonomous vehicle ...
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Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors
Using sensor data from multiple modalities presents an opportunity to en...
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Multimodal Sensor Fusion with Differentiable Filters
Leveraging multimodal information with recursive Bayesian filters improv...
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GRAC: Self-Guided and Self-Regularized Actor-Critic
Deep reinforcement learning (DRL) algorithms have successfully been demo...
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Learning Topological Motion Primitives for Knot Planning
In this paper, we approach the challenging problem of motion planning fo...
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Learning User-Preferred Mappings for Intuitive Robot Control
When humans control drones, cars, and robots, we often have some preconc...
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Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
We consider the problem of dynamically allocating tasks to multiple agen...
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Probabilistic 3D Multi-Object Tracking for Autonomous Driving
3D multi-object tracking is a key module in autonomous driving applicati...
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Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects
We demonstrate model-based, visual robot manipulation of linear deformab...
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Object-Centric Task and Motion Planning in Dynamic Environments
We address the problem of applying Task and Motion Planning (TAMP) in re...
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Accurate Vision-based Manipulation through Contact Reasoning
Planning contact interactions is one of the core challenges of many robo...
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Learning to Scaffold the Development of Robotic Manipulation Skills
Learning contact-rich, robotic manipulation skills is a challenging prob...
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Learning Task-Oriented Grasping from Human Activity Datasets
We propose to leverage a real-world, human activity RGB datasets to teac...
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Learning Hierarchical Control for Robust In-Hand Manipulation
Robotic in-hand manipulation has been a long-standing challenge due to t...
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UniGrasp: Learning a Unified Model to Grasp with N-Fingered Robotic Hands
To achieve a successful grasp, gripper attributes including geometry and...
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MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences
Understanding dynamic 3D environment is crucial for robotic agents and m...
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Learning from My Partner's Actions: Roles in Decentralized Robot Teams
When teams of robots collaborate to complete a task, communication is of...
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Learning an Action-Conditional Model for Haptic Texture Generation
Rich haptic sensory feedback in response to user interactions is desirab...
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Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biases
Endowing robots with human-like physical reasoning abilities remains cha...
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Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks
Contact-rich manipulation tasks in unstructured environments often requi...
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Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
Reinforcement Learning (RL) of contact-rich manipulation tasks has yield...
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Learning Manipulation under Physics Constraints with Visual Perception
Understanding physical phenomena is a key competence that enables humans...
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Learning to Estimate Pose and Shape of Hand-Held Objects from RGB Images
We develop a system for modeling hand-object interactions in 3D from RGB...
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Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
Contact-rich manipulation tasks in unstructured environments often requi...
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Leveraging Contact Forces for Learning to Grasp
Grasping objects under uncertainty remains an open problem in robotics r...
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Grasp success prediction with quality metrics
Current robotic manipulation requires reliable methods to predict whethe...
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ClusterNet: Instance Segmentation in RGB-D Images
We propose a method for instance-level segmentation that uses RGB-D data...
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Motion-based Object Segmentation based on Dense RGB-D Scene Flow
Given two consecutive RGB-D images, we propose a model that estimates a ...
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Acquiring Target Stacking Skills by Goal-Parameterized Deep Reinforcement Learning
Understanding physical phenomena is a key component of human intelligenc...
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Combining learned and analytical models for predicting action effects
One of the most basic skills a robot should possess is predicting the ef...
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Latest Datasets and Technologies Presented in the Workshop on Grasping and Manipulation Datasets
This paper reports the activities and outcomes in the Workshop on Graspi...
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Depth-Based Object Tracking Using a Robust Gaussian Filter
We consider the problem of model-based 3D-tracking of objects given dens...
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Robust Gaussian Filtering using a Pseudo Measurement
Many sensors, such as range, sonar, radar, GPS and visual devices, produ...
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