CHARM: Collaborative, Human-Focused, Assistive Robotics for Manufacturing

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FP7 DARWIN: Dexterous Assembler Robot Working with embodied Intelligence

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FP7 ROBO-HOW: Web-enabled and experience-based cognitive robots that learn complex everyday manipulation tasks

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FP7 TOMSY: Topology Based Motion Synthesis for Dexterous Manipulation

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FP7 WALK-MAN: Whole-body Adaptive Locomotion and Manipulation

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FP7 CODYCO: Whole-body compliant dynamical contacts in cognitive robotics

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FP7 PACMAN: Probabilistic and compositional representations for object manipulation

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FP7 XPERIENCE: Robots boostrapped through learning from experience

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FP7 DEXMART: DEXterous and autonomous dual-arm/hand robotic manipulation with sMART sensory-motor skills: A bridge from natural to artificial cognition

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FP7 HANDLE: Developmental pathway towards autonomy and dexterity in robot in-hand manipulation

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FP7 GRASP: Emergence of Cognitive Grasping through Introspection, Emulation and Surprise

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FP7 ECHORD Experiment: "ActReMa - ActiveRecognition and Manipulation of Simple Parts Exploiting 3D Information"

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This experiment investigates a hyper-flexible cells scenario. In particular, we consider the following setting: A robot delivers parts to a process station. The parts are made available to the workspace of the robot in transport boxes that are not required to be packed in a systematic way. With its onboard 3D laser scanning sensor, the robot recognizes and identifies the topmost objects in the boxes. It grasps the parts out of the box and moves them to the station for further processing. The parts can be shaped nearly arbitrarily. We only assume that parts can be approximated by geometric shape primitives like e.g. cylinders or spheres. A new part type can be learned in a matter of minutes simply by presenting an exemplar to the robot.

The major challenges arising in this setting which will be addressed in the experiment are:

  • Robust and efficient recognition of the composition of objects from measurements of a 3D laser scanning device. 
  • Efficient exploration of the part arrangement in the transport boxes to handle occlusions.
  • Flexible grasp and motion planning for a robot under real-time constraints in a semi-structured environment, i.e. when the arrangement of parts and transport boxes is variable.

www.ais.uni-bonn.de/nimbro/@Home">http://www.ais.uni-bonn.de/nimbro/@Home
DFG Research Group "Learning Humanoid Robots"
funded within the Emmy Noether Programme

The cognitive service robots Dynamaid and Cosero have been developed for tasks in domestic environments.
They won the RoboCup 2011 and 2012 competitions.

The Autonomous Robotic Manipulation (ARM) Lab

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Overview of projects in the ARM lab.

Control Systems Laboratory

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Selection of projects relative to mobile manipulation (as of End 2012):

Autonomous Servicing of On-Orbit Space Systems from Robotic Systems (NSRF)

Identification and Assessment of Existing Terrestrial Micro-systems and Micro-technologies for Space Robotics (ESA)

Development of a Flexible and Reliable Automated Warehouse System

Modeling and Control of Microrobotic Systems

MiCRoN: MIniature Co-operative RObots advancing towards the Nano-range

Autonomous Inspection of Subsea Telecommunication Cables, Power Cables and Pipelines (EU)

CS Robotics Lab

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We are developing a grasp testbed for studying the process of grasp acquisition in human and robotic systems.  The system is built around our Barrett WAM/Hand system on which we have implemented a hand-frame impedance controller, a Natural Point body tracking system, and multibody dynamic simulation capabiltiy.  It will be further enhanced with the results of a recent NRI grant focused on Bayesian filtering for grasp perception.

HERB

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Our bimanual mobile manipulation platform, with two Barrett WAM arms atop a completely redesigned chassis with a Segway RMP 200 base.

Robotics and Computer Vision

Projects pertaining to mobile manipulation

Currently funded projects:

Human-Robot Interaction for Assistive Applications (HRIAA), funded by ANR Chair d'Excellence Control Software Achitecture for Robust Robot Manipulation (Carroman), funded by ADT INRIA

BesMan - Behaviours for Mobile Manipulation

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The main goal of the project BesMan is the development of one- and two-arm manipulation procedures as well as the learning of new situation-specific behaviors by means of a machine learning platform.

IMPERA - Integrated Mission Planning for Distributed Robot Systems

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The goal of the research project IMPERA is the development of strategies for distributed mission and task planning. An application example is the exploration of unknown, lunar environment using a team of mobile robots

Please publish modules in offcanvas position.

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