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Thread: Rollin' Justin, humanoid robot, Robotics and Mechatronics Center, Cologne, Germany

  1. #1

    Rollin' Justin, humanoid robot, Robotics and Mechatronics Center, Cologne, Germany


  2. #2


    Rollin' Justin Robot Catches Balls Tossed in its Direction

    Uploaded on Apr 27, 2011

    New controllers from DLR allow Rollin' Justin to catch balls tossed in its direction.

  3. #3


    Rollin' Justin: Window Cleaning

    Published on Apr 25, 2014

    Object-Centered Hybrid Reasoning for Whole-Body Mobile Manipulation
    This video features the humanoid robot Rollin' Justin of the German Aerospace Center (DLR), while wiping a window as a typical example for whole-body mobile manipulation. Hybrid reasoning is used to determine the optimal position of the robot regarding the task to be executed. Furthermore, the control parameters for the compliant behavior are specified during the planning phase. This way uncertainties and external disturbances can be compensated by the robot, while the task is accomplished.

  4. #4


    Humanoid robot Justin dances Pulp Fiction song

    Published on Jul 24, 2012

    Humanoid robot Justin (developed by DLR, Germany) dances "Jackrabbit Slim's Twist Contest" from the movie Pulp Fiction

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    Towards Intelligent Compliant Service Robots

    Published on Jan 15, 2015

    Towards Intelligent Compliant Service Robots
    Daniel Leidner and Alexander Dietrich
    Institute of Robotics and Mechatronics, German Aerospace Center (DLR)

  6. #6


    Planning and Execution of Daily Cleaning Tasks with the Humanoid Service Robot Rollin' Justin

    Published on Mar 8, 2016

    Universal robotic agents are envisaged to perform a wide range of manipulation tasks in everyday environments. A common action observed in many household chores is wiping, such as the absorption of spilled water with a sponge, skimming breadcrumbs off the dining table, or collecting shards of a broken mug using a broom. To cope with this versatility, the agents have to represent the tasks on a high level of abstraction. In this work, we propose to represent the medium in wiping tasks (\eg water, breadcrumbs, or shards) as generic particle distribution. This representation enables us to represent wiping tasks as the desired state change of the particles, which allows the agent to reason about the effects of wiping motions in a qualitative manner. Based on this, we develop three prototypical wiping actions for the generic tasks of absorbing, collecting and skimming. The Cartesian wiping motions are resolved to joint motions exploiting the free degree of freedom of the involved tool. Furthermore, the workspace of the robotic manipulators is used to reason about the reachability of wiping motions. We evaluate our methods in simulated scenarios, as well as in a real experiment with the robotic agent Rollin' Justin.

    Daniel Leidner, Wissam Bejjani, Alin Albu-Sch?ffer, and Michael Beetz "Robotic Agents Representing, Reasoning, and Executing Wiping Tasks for Daily Household Chores", in Proc. of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Singapore, May 2016.

    A draft version of the research paper is located at: https://elib.dlr.de/103272

  7. #7


    An approach to combine balancing with hierarchical whole-body control for legged humanoid robots

    Uploaded on May 20, 2016

    “An Approach to Combine Balancing with Hierarchical Whole-Body Control for Legged Humanoid Robots,” by Bernd Henze, Alexander Dietrich, and Christian Ott from German Aerospace Center (DLR). Presented at ICRA 2016.

  8. #8


    Agile Justin classifies materials by touch using deep learning

    Published on Oct 18, 2016

    In this paper we show that material classification purely based on the spatio-temporal signal of a flexible tactile skin mounted on the finger tip of the advanced humanoid robot Agile Justin can be robustly performed in a real world setting. We develop a convolutional deep learning network architecture which is directly fed with the raw 24000 dimensional sensor signal of the tactile skin. The network with its 16 million weights is trained from only 540 samples and reaches a classification accuracy of up to 97.3%.

    S. Baishya and B. Bäuml. Robust material classification with a tactile skin using deep learning. In Proc. IEEE International Conference on Intelligent Robots and Systems, 2016.

  9. #9


    Rollin' Justin infers the effects of wiping motions using haptic perception

    Published on Nov 14, 2016

    Future service robots are expected to achieve high-quality task performance for everyday household chores. Some of the most frequent tasks in this domain are related to wiping of surfaces, such as vacuuming the floor, sweeping dust, or cleaning windows. However, the performance for these tasks is not directly observable as small dirt particles, dust, and residual water are hardly perceivable by means of computer vision. In this work we propose to utilize haptic perception paired with a qualitative effect representation to reason about the task performance of robotic wiping motions despite poor visual information. In particular, we relate the desired contact force to the measured end-effector force in order to simulate the effect of previously executed wiping motions. This way we are not just able to distinguish good from bad contact situations, but also replan recovery motions w.r.t. the effect-space to accomplish the commanded cleaning task subsequently. We evaluate our approach in a set of experiments with the robot Rollin' Justin.

    Daniel Leidner and Michael Beetz "Inferring the Effects of Wiping Motions based on Haptic Perception", in Proc. of the International Conference on Humanoid Robots (ICHR), Mexico, November 2016.

    A draft version of the research paper is located at: elib.dlr.de/107678

  10. #10


    Alexander Gerst controls Justin humanoid robot from the ISS

    Published on Aug 17, 2018

    As part of ESA-led METERON (Multi-Purpose End-to-End Robotic Operations Network) project, Astronaut Alexander Gerst supervised and controlled the humanoid robot Justin to perform a series of tasks.

    Credit:
    Deutsche Zentrum für Luft- und Raumfahrt (DLR)
    METERON project
    Astronaut Alexander Gerst and humanoid robot Justin
    17 August 2018

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