Multi-Source Fusion for Voxel-Based 7-DoF Grasping Pose Estimation

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Controlling complex tasks in robotic systems, such as circular motion for cleaning or following curvy lines, can be dealt with using nonlinear vector fields. This article introduces a novel approach called the rotational obstacle avoidance method (ROAM) fo ...

New particle formation (NPF) substantially contributes to global cloud condensation nuclei (CCN), and their climate impacts. Individual NPF events are also thought to increase local CCN, cloud droplet number (CDN), and cloud albedo. High resolution simulat ...

Arctic clouds are sensitive to atmospheric particles since these are sometimes in such low concentrations that clouds cannot always form under supersaturated water vapor conditions. This is especially true in the late summer, when aerosol concentrations ar ...

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

The representation of Arctic clouds and their phase distributions, i.e., the amount of ice and supercooled water, influences predictions of future Arctic warming. Therefore, it is essential that cloud phase is correctly captured by models in order to accur ...

In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

Humans coordinate the abundant degrees of freedom (DoFs) of hands to dexterously perform tasks in everyday life. We imitate human strategies to advance the dexterity of multi-DoF robotic hands. Specifically, we enable a robot hand to grasp multiple objects ...

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed "Arctic amplification" ...

We propose a method to extract orthogonal views of facades from photogrammetric models of cities. This method was applied to extract all facades of the city of Venice. The result images open up new areas of research in architectural history. ...

Haptic perception of softness is a unique feature of the human skin that relies on the concurrent measurements of the lateral deformation and compression of the skin during object manipulation. This is challenging to implement in robotics because of combin ...

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle t ...

Myoelectric prostheses allow users to recover lost functionality by controlling a robotic device with their remaining muscle activity. Commercial devices usually use a two-recording-channel system placed on specific muscles to control a single degree of fr ...

Clouds are omnipresent in the Earth's atmosphere. Their phase composition significantly modulates their interaction with solar and terrestrial radiation, as well as precipitation formation. Particularly for clouds containing both phases, known as mixed-pha ...

The following data contain the information and files, which are required to recreate and build the experimental setup that is described in the Laboratory manual. Further details can be found in the associated publication “A graduate laboratory experiment t ...

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approa ...

Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

Multi-Source Fusion for Voxel-Based 7-DoF Grasping Pose Estimation

Chattez avec Graph Search

Avoidance of Concave Obstacles Through Rotation of Nonlinear Dynamics

New Particle Formation Events Can Reduce Cloud Droplets in Boundary Layer Clouds at the Continental Scale

Highly Hygroscopic Aerosols Facilitate Summer and Early‐Autumn Cloud Formation at Extremely Low Concentrations Over the Central Arctic Ocean

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Investigating neural resource allocation in the sensorimotor control of extra limbs

Simulations of primary and secondary ice production during an Arctic mixed-phase cloud case from the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) campaign

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Exploration-based model learning with self-attention for risk-sensitive robot control

Exploiting Kinematic Redundancy for Robotic Grasping of Multiple Objects

Evaluating the effect of sparse convolutions on point cloud compression

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

The Skin of Venice: Automatic Facade Extraction from Point Clouds

Liquid Metal-Based Sensor Skin Enabling Haptic Perception of Softness

Learning and optimization of anticipatory feedback controllers for robot manipulation

MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency

Improving hand prosthesis control with advanced single-finger proportional decoding and robotic shared control

The role of secondary ice production in mixed-phase clouds

Acoustic Levitation apparatus (Robotics Practicals)

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Morphological flexibility in robotic systems through physical polygon meshing