13 accepted papers
Powered lower limb exoskeletons (LLEs) have emerged as wearable robots designed to augment users’ locomotion capabilities, offering mechanical support and additional power for both healthy and impaired subjects. However, current assistive exoskeletons are limited by predefined motion trajectories, h
Semantic segmentation of point clouds is an essential task for understanding the environment in autonomous driving and robotics. Recent range-based works achieve real-time efficiency, while point- and voxel-based methods produce better results but are affected by high computational complexity. Moreo…
Panoramic cameras offer a 4π steradian field of view, which is desirable for tasks like people detection and tracking since nobody can exit the field of view. Despite the recent diffusion of low-cost panoramic cameras, their usage in robotics remains constrained by the limited availability of datase…
Robotic waste sorting poses significant challenges in both perception and manipulation, given the extreme variability of objects that should be recognized on a cluttered conveyor belt. While deep learning has proven effective in solving complex tasks, the necessity for extensive data collection and…
Hand-eye calibration is the problem of estimating the spatial transformation between a reference frame, usually the base of a robot arm or its gripper, and the reference frame of one or multiple cameras. Generally, this calibration is solved as a non-linear optimization problem, what instead is rare…
Robot grasping has been widely studied in the last decade. Recently, Deep Learning made possible to achieve remarkable results in grasp pose estimation, using depth and RGB images. However, only few works consider the choice of the object to grasp. Moreover, they require a huge amount of data for ge…
This paper describes a calibration method for RGB-D camera networks consisting of not only static overlapping, but also dynamic and non-overlapping cameras. The proposed method consists of two steps: online visual odometry-based calibration and depth image-based calibration refinement. It first esti…
We present a 3D capsule module for processing point clouds that is equivariant to 3D rotations and translations, as well as invariant to permutations of the input points. The operator receives a sparse set of local reference frames, computed from an input point cloud and establishes end-to-end trans…
This letter describes a novel hand-eye calibration technique based on reprojection error minimization. In contrast to traditional hand-eye calibration methods, the proposed method directly takes images of the calibration pattern and does not require to explicitly estimate the camera pose for each in
This paper shows and evaluates a novel approach to integrate a non-invasive Brain-Computer Interface (BCI) with the Robot Operating System (ROS) to mentally drive a telepresence robot. Controlling a mobile device by using human brain signals might improve the quality of life of people suffering from…
Applications that provide location related services need to understand the environment in which humans live such that verbal references and human interaction are possible. We formulate this semantic labelling task as the problem of learning the semantic labels from the perceived 3D structure. In thi…
This paper deals with the problem of detecting fallen people lying on the floor by means of a mobile robot equipped with a 3D depth sensor. In the proposed algorithm, inspired by semantic segmentation techniques, the 3D scene is over-segmented into small patches. Fallen people are then detected by m…
This paper presents a fast and robust multiple object tracking algorithm based on an RGB-D version of the MeanShift tracking algorithm and exploiting RGB-D camera networks when multiple RGB-D sensors are available. The original Mean-Shift algorithm has been improved in three ways. First, a color-dep…