Humanoid Robot Armar
Uploaded on Jun 25, 2010
Developer and manufacturer - Humanoids and Intelligence Systems Lab
Home Page - his.anthropomatik.kit.edu/english/241.php
Armar 3 on Wikipedia
High Performance Humanoid Technologies Lab (H2T) - h2t.anthropomatik.kit.edu
Professor on Humanoid Robotics Systems - Tamim Asfour
Controlling the ARMAR III with a tablet
Published on Apr 3, 2014
In this video, intuitive control of the humanoid robot ARMAR III with a tablet is shown.
The android application to control the robot was developed by a group of students at KIT during their internship at our institute.
Programming a humanoid robot assistant kitchen
Published on May 5, 2014
The students had to extend the task, the capabilities of our kitchen assistant robot ARMAR III. You should combine existing capabilities complex tasks such as grasping and placing as bringing the ingredients of a recipe.
Validation of Whole-Body Loco-Manipulation Affordances for Pushability and Liftability
Published on Nov 6, 2015
This video shows the results presented in:
P. Kaiser, M. Grotz, E. E. Aksoy, M. Do, N. Vahrenkamp and T. Asfour, Validation of Whole-Body Loco-Manipulation Affordances for Pushability and Liftability, IEEE/RAS International Conference on Humanoid Robots (Humanoids), 2015
Abstract
Autonomous robots that are intended to work in disaster scenarios like collapsed or contaminated buildings need to be able to efficiently identify action possibilities in unknown environments. This includes the detection of environmental elements that allow interaction, such as doors or debris, as well as the utilization of fixed environmental structures for stable whole-body loco-manipulation. Affordances that refer to whole- body actions are especially valuable for humanoid robots as the necessity of stabilization is an integral part of their control strategies.
Based on our previous work we propose to apply the concept of affordances to actions of stable whole-body loco- manipulation, in
particular to pushing and lifting of large objects. We extend our perceptual pipeline in order to build large- scale representations of
the robot’s environment in terms of environmental primitives like
planes, cylinders and spheres. A rule-based system is employed to derive whole-body affordance hypotheses from these primitives, which are then subject to validation by the robot. An experimental evaluation demonstrates our progress in detection, validation and utilization of whole-body affordances.
Integration of natural language understanding, robot's memory and planning in a humanoid robot
Published on Jul 28, 2016
This video shows the results of the approach presented in the paper "Integration of Multi-Purpose Natural Language Understanding, Robot's Memory, and Planning in a Humanoid Robot Platform?".
We introduce a framework that allows the robot to understand natural language, generate symbolic representations of its sensorimotor experience, generate complex plans according to the current world state, monitor plan execution, replace missing objects and suggest object locations. The framework is implemented within the robot development environment ArmarX and is based on the concept of structural bootstrapping developed in the context of the European project Xperience. We test the framework on the humanoid robot ARMAR-III in the kitchen environment with a complex scenario about setting a table and preparing a salad, which is shown in this video.
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