226 citations · 490 across the 18 of their papers we have counts for
19 papers
Motion Generation With Environmental Constraints
Előd Páll, Oliver Brock
Robot motion planning faces challenges in high-dimensional spaces and uncertain environments, often constrained by the need for collision-free motions. We advocate an alternative a…
Acoustic Sensing for Universal Jamming Grippers
Lion Weber, Theodor Wienert, Martin Splettstößer +2
Universal jamming grippers excel at grasping unknown objects due to their compliant bodies. Traditional tactile sensors can compromise this compliance, reducing grasping performanc…
In-Hand Cube Reconfiguration: Simplified
Sumit Patidar, Adrian Sieler, Oliver Brock
We present a simple approach to in-hand cube reconfiguration. By simplifying planning, control, and perception as much as possible, while maintaining robust and general performance…
Dexterous Soft Hands Linearize Feedback-Control for In-Hand Manipulation
Adrian Sieler, Oliver Brock
This paper presents a feedback-control framework for in-hand manipulation (IHM) with dexterous soft hands that enables the acquisition of manipulation skills in the real-world with…
Augmentation for Learning From Demonstration with Environmental Constraints
Xing Li, Manuel Baum, Oliver Brock
We introduce a Learning from Demonstration (LfD) approach for contact-rich manipulation tasks with articulated mechanisms. The extracted policy from a single human demonstration ge…
Passive and Active Acoustic Sensing for Soft Pneumatic Actuators
Vincent Wall, Gabriel Zöller, Oliver Brock
We propose a sensorization method for soft pneumatic actuators that uses an embedded microphone and speaker to measure different actuator properties. The physical state of the actu…
A Virtual 2D Tactile Array for Soft Actuators Using Acoustic Sensing
Vincent Wall, Oliver Brock
We create a virtual 2D tactile array for soft pneumatic actuators using embedded audio components. We detect contact-specific changes in sound modulation to infer tactile informati…
One Object at a Time: Accurate and Robust Structure From Motion for Robots
Aravind Battaje, Oliver Brock
A gaze-fixating robot perceives distance to the fixated object and relative positions of surrounding objects immediately, accurately, and robustly. We show how fixation, which is t…
"The World Is Its Own Best Model": Robust Real-World Manipulation Through Online Behavior Selection
Manuel Baum, Oliver Brock
Robotic manipulation behavior should be robust to disturbances that violate high-level task-structure. Such robustness can be achieved by constantly monitoring the environment to o…
Surprisingly Robust In-Hand Manipulation: An Empirical Study
Aditya Bhatt, Adrian Sieler, Steffen Puhlmann +1
We present in-hand manipulation skills on a dexterous, compliant, anthropomorphic hand. Even though these skills were derived in a simplistic manner, they exhibit surprising robust…
RBO Hand 3 -- A Platform for Soft Dexterous Manipulation
Steffen Puhlmann, Jason Harris, Oliver Brock
We present the RBO Hand 3, a highly capable and versatile anthropomorphic soft hand based on pneumatic actuation. The RBO Hand 3 is designed to enable dexterous manipulation, to fa…
A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition
Tessa J. Pannen, Steffen Puhlmann, Oliver Brock
Soft robotics is an emerging field that yields promising results for tasks that require safe and robust interactions with the environment or with humans, such as grasping, manipula…
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot +17
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning metho…
The RBO Dataset of Articulated Objects and Interactions
Roberto Martín-Martín, Clemens Eppner, Oliver Brock
We present a dataset with models of 14 articulated objects commonly found in human environments and with RGB-D video sequences and wrenches recorded of human interactions with them…
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors
Rico Jonschkowski, Divyam Rastogi, Oliver Brock
We present differentiable particle filters (DPFs): a differentiable implementation of the particle filter algorithm with learnable motion and measurement models. Since DPFs are end…
The Limits and Potentials of Deep Learning for Robotics
Niko Sünderhauf, Oliver Brock, Walter Scheirer +8
The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and machine learning com…
Interactive Perception: Leveraging Action in Perception and Perception in Action
Jeannette Bohg, Karol Hausman, Bharath Sankaran +4
Recent approaches in robotics follow the insight that perception is facilitated by interaction with the environment. These approaches are subsumed under the term of Interactive Per…
Analysis and Observations from the First Amazon Picking Challenge
Nikolaus Correll, Kostas E. Bekris, Dmitry Berenson +7
This paper presents a overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to desi…
Patterns for Learning with Side Information
Rico Jonschkowski, Sebastian Höfer, Oliver Brock
Supervised, semi-supervised, and unsupervised learning estimate a function given input/output samples. Generalization of the learned function to unseen data can be improved by inco…