8 accepted papers
This work proposes OcLe-CNN, a sparse octree-based Convolutional Neural Network (CNN) for 3D occupancy prediction. Occupancy prediction involves the inference of the occupancy probability of unobserved space. OcLe-CNN processes an octree-like data structure resulting in a reduced memory usage, as re
Solving complex robot manipulation tasks requires a Task and Motion Planner (TAMP) that searches for a sequence of symbolic actions, i.e. a task plan, and also computes collision-free motion paths. As the task planner and the motion planner are closely interconnected TAMP is considered a challenging
Depth images usually contain pixels with invalid measurements. This paper presents a deep learning approach that receives as input a partially-known volumetric model of the environment and a camera pose, and it predicts the probability that a pixel would contain a valid depth measurement if a camera…
In this work we present a novel method to plan the next best view of a depth camera by leveraging on a Convolutional Neural Network (CNN), and on a probabilistic occupancy map of the environment for ray casting operations. In particular, a hybrid approach is introduced that exploits the convolutiona
This work presents an approach for part-based grasp planning in point clouds. A complete pipeline is proposed that allows a robot manipulator equipped with a range camera to perform object detection, categorization, segmentation into meaningful parts, and part-based semantic grasping. A supervised i
This work presents an approach for humanoid Next Best View (NBV) planning that exploits full body motions to observe objects occluded by obstacles. The task is to explore a given region of interest in an initially unknown environment. The robot is equipped with a depth sensor, and it can perform bot…
Next best view (NBV) planning is a central task for automated three-dimensional (3-D) reconstruction in robotics. The most expensive phase of NBV computation is the view simulation step, where the information gain of a large number of candidate sensor poses are estimated. Usually, information gain i
This paper presents an algorithm for surfel color and position enhancement from RGB-D data acquired across multiple image frames. Surfel-based reconstruction algorithms associate each RGB-D frame pixel to a surfel in the model. As the reconstruction progresses, surfel color and position are the aver…