FG Robotics

25 Items

Recent Submissions
Active Acoustic Contact Sensing for Soft Pneumatic Actuators

Zöller, Gabriel ; Wall, Vincent ; Brock, Oliver (2020-02)

Supplementary data to our publication Zöller, Gabriel, Vincent Wall, and Oliver Brock. "Active Acoustic Contact Sensing for Soft Pneumatic Actuators." 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020.

Learning to explore the structure of kinematic objects in a virtual environment

Buckmann, Marcus ; Gaschler, Robert ; Höfer, Sebastian ; Loeben, Dennis ; Frensch, Peter A. ; Brock, Oliver (2015-04-07)

The current study tested the quantity and quality of human exploration learning in a virtual environment. Given the everyday experience of humans with physical object exploration, we document substantial practice gains in the time, force, and number of actions needed to classify the structure of virtual chains, marking the joints as revolute, prismatic, or rigid. In line with current work on sk...

Robust motion generation for mobile manipulation — integrating control and planning under uncertainty

Sieverling, Arne (2019)

This thesis contributes to algorithmic approaches for the motion generation problem for mobile manipulators. This problem is unsolved in unstructured environments, where the robot does not have access to precise models but must infer the state of the world with its sensors. The challenges for motion generation in these problems arise from the uncertainty prevalent in real world sensors, the dif...

Robot grasping by exploiting compliance and environmental constraints

Eppner, Clemens (2019)

Grasping is a crucial skill for any autonomous system that needs to alter the physical world. The complexity of robot grasping stems from the fact that any solution comprises various components: Hand design, control, perception, and planning all affect the success of a grasp. Apart from picking solutions in well-defined industrial scenarios, general grasping in unstructured environment is still...

Strain sensor placement evaluation

Wall, Vincent ; Zöller, Gabriel ; Brock, Oliver (2019-05)

This dataset contains sensor data acquired (pressure, strain, and Motion Capture data) of PneuFlex with various sensor layouts.

Soft hand teleoperation

Erdogan, Can ; Schröder, Armin ; Eppner, Clemens ; Brock, Oliver (2019-05)

The dataset consists of rosbags that contain the cyber-glove and force-torque sensor data of teleoperation experiments.

Stiffness control by cocontraction

Höppner, Hannes (2019-05)

The dataset provides data on the coupling between force and stiffness during pinch-grasping by humans, and the possibility to decouple the coupling by cocontraction. The dataset contains motion tracking data, grip force data and muscle contraction measurements.

RBO Hand 2 simulation model

Pozzi, Maria ; Miguel, Eder ; Deimel, Raphael ; Malvezzi, Monica ; Bickel, Bernd ; Brock, Oliver ; Prattichizzo, Domenico (2019-05)

This dataset contains readily usable FEM models and code for simulating a single PneuFlex actuator, which is used in the RBO Hands.

Co-design of Plan and Environment

Abele, Jessica ; Brock, Oliver (2019-04-08)

This dataset contains CAD models of the designed environment constraints which optimize the wall and corner EC primitives.

Environmental Constraints Exploitation

Páll, Előd ; Abele, Jessica ; Sieverling, Arne ; Eppner, Clemens ; Wortmann, Johannes ; Erdogan, Can ; Brock, Oliver (2019-04-08)

This dataset contains point cloud data of the experimental setup, links to the repositories of EC primitive detectors and grasp planner.

Human hand grasping experiments: raw grasping data

Heinemann, Fabian ; Puhlmann, Steffen ; Eppner, Clemens ; Álvarez-Ruiz, José ; Meartens, Marianne ; Brock, Oliver (2019-05)

This dataset contains grasping data from human grasping experiments. The sensors used are: FT-Sensor (for contact forces), Touchpad (contact traces), MoCap-System (Hand position and orientation), Cyberglove (finger postures).

Human hand grasping experiments: annotated grasps segments

Heinemann, Fabian ; Puhlmann, Steffen ; Eppner, Clemens ; Álvarez-Ruiz, José ; Meartens, Marianne ; Brock, Oliver (2019-05)

This dataset contains segmented labelling data from human hand grasping experiments. The human experiment data was labelled by 3 independent labellers.

State Representation Learning with Robotic Priors for Partially Observable Environments Data

Morik, Marco ; Rastogi, Divyam ; Brock, Oliver (2019)

We introduce Recurrent State Representation Learning (RSRL) to tackle the problem of state representation learning in robotics for partially observable environments. To learn low dimensional state representations, we combine a Long Short Term Memory network with robotic priors. RSRL introduces new priors with landmarks and combines them with existing robotics priors in literature to train the r...

Chip Multiprocessor Traffic Models Providing Consistent Multicast and Spatial Distributions

Tutsch, Dietmar ; Lüdtke, Daniel (2008)

Chip multiprocessors (CMPs) have become the center of attention in recent years. They consist of multiple processor cores on a single chip. These cores are connected on-chip by a bus or, if many cores are involved, by an appropriate network. To investigate how a multicore processor behaves dependent on the chosen network-on-chip topology, a corresponding model must be established for performanc...

Leveraging novel information for coarse-grained prediction of protein motion

Putz, Ines (2018)

Proteins are involved in almost all functions in our cells due to their ability to combine conformational motion with chemical specificity. Hence, information about the motions of a protein provides insights into its function. Proteins move on a rugged energy landscape with many local minima, which is imposed on their high-dimensional conformational space. Exhaustive sampling of this space exce...

EPSILON-CP: using deep learning to combine information from multiple sources for protein contact prediction

Stahl, Kolja ; Schneider, Michael ; Brock, Oliver (2017-06-17)

Background Accurately predicted contacts allow to compute the 3D structure of a protein. Since the solution space of native residue-residue contact pairs is very large, it is necessary to leverage information to identify relevant regions of the solution space, i.e. correct contacts. Every additional source of information can contribute to narrowing down candidate regions. Therefore, recent met...

Learning robotic perception through prior knowledge

Jonschkowski, Rico (2018)

Intelligent robots must be able to learn; they must be able to adapt their behavior based on experience. But generalization from past experience is only possible based on assumptions or prior knowledge (priors for short) about how the world works. I study the role of these priors for learning perception. Although priors play a central role in machine learning, they are often hidden in the deta...

No Free Lunch in Ball Catching: A Comparison of Cartesian and Angular Representations for Control

Höfer, Sebastian ; Raisch, Jörg ; Toussaint, Marc ; Brock, Oliver (2018)

How to run most effectively to catch a projectile, such as a baseball, that is flying in the air for a long period of time? The question about the best solution to the ball catching problem has been subject to intense scientific debate for almost 50 years. It turns out that this scientific debate is not focused on the ball catching problem alone, but revolves around the research question what c...

Leveraging problem structure in interactive perception for robot manipulation of constrained mechanisms

Martín-Martín, Roberto (2018)

In this thesis we study robot perception to support a specific type of manipulation task in unstructured environments, the mechanical manipulation of kinematic degrees of freedom. In these tasks the goal of the robot is to create controlled motion, i.e. to change configuration of the kinematic degrees of freedom (DoF) of the objects in the environment. Often, the environment contains articulate...

Exploitation of environmental constraints in human and robotic grasping

Eppner, Clemens ; Deimel, Raphael ; Álvarez-Ruiz, José ; Maertens, Marianne ; Brock, Oliver (2015)

We investigate the premise that robust grasping performance is enabled by exploiting constraints present in the environment. These constraints, leveraged through motion in contact, counteract uncertainty in state variables relevant to grasp success. Given this premise, grasping becomes a process of successive exploitation of environmental constraints, until a successful grasp has been establish...