Search Results for author:
Found 14 papers, 7 papers with code
Teacher Network Calibration Improves Cross-Quality Knowledge Distillation
We investigate cross-quality knowledge distillation (CQKD), a knowledge distillation method where knowledge from a teacher network trained with full-resolution images is transferred to a student network that takes as input low-resolution images.
Partially Observable Markov Decision Processes in Robotics: A Survey
Noisy sensing, imperfect control, and environment changes are defining characteristics of many real-world robot tasks.
CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds
In contrast, this domain gap is considerably smaller and easier to fill for depth information.
Multi-agent active perception with prediction rewards
The accuracy is quantified by a centralized prediction reward determined by a centralized decision-maker who perceives the observations gathered by all agents after the task ends.
Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization
We consider the problem of creating a 3D model using depth images captured by a team of multiple robots.
6D Object Pose Regression via Supervised Learning on Point Clouds
We use depth information represented by point clouds as the input to both deep networks and geometry-based pose refinement and use separate networks for rotation and translation regression.
Information Gathering in Decentralized POMDPs by Policy Graph Improvement
Decentralized policies for information gathering are required when multiple autonomous agents are deployed to collect data about a phenomenon of interest without the ability to communicate.
Multi-label Object Attribute Classification using a Convolutional Neural Network
With this inspiration, a deep convolutional neural network for low-level object attribute classification, called the Deep Attribute Network (DAN), is proposed.
Occlusion Resistant Object Rotation Regression from Point Cloud Segments
Rotation estimation of known rigid objects is important for robotic applications such as dexterous manipulation.
Saliency-guided Adaptive Seeding for Supervoxel Segmentation
We propose a new saliency-guided method for generating supervoxels in 3D space.
Object proposal generation applying the distance dependent Chinese restaurant process
In application domains such as robotics, it is useful to represent the uncertainty related to the robot's belief about the state of its environment.
Multi-Robot Active Information Gathering with Periodic Communication
We address the problem of coordinating the actions of a team of robots with periodic communication capability executing an information gathering task.
Optimal Sensing via Multi-armed Bandit Relaxations in Mixed Observability Domains
Sequential decision making under uncertainty is studied in a mixed observability domain.
Planning for robotic exploration based on forward simulation
We address the problem of controlling a mobile robot to explore a partially known environment.
Robotics Systems and Control 90C40
