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Robust Locomotion of a Humanoid Robot Considering Grasped Objects

Reimold, Florian (2016):
Robust Locomotion of a Humanoid Robot Considering Grasped Objects.
Department of Computer Science (SIM), Technische Universitaet Darmstadt, Department of Computer Science (SIM), [Master Thesis]

Abstract

During the DARPA Robotics Challenge (DRC) in 2015, robots had to solve tasks in a disaster scenario motivated by the Fukushima nuclear incident. The robots had to be able to operate in an environment, which was designed for humans. This encouraged the development of humanoid-shaped robots. One task was to use a battery-powered drill to cut a hole in a wall. During the DRC, those tools were located right next to the wall, but in real world scenarios, it cannot be assumed to find the proper tool directly next to the place where it is needed. In most cases, the robot has to carry a tool across the site to complete the task. Therefore, a humanoid robot must be able to carry a needed tool without falling down. In this thesis, we investigate an approach how to enable a THOR-MANG robot to walk and carry objects without falling. We applied different walking approaches and finally decided to extend Missura’s Capture Step Framework to enable the robot to carry tools. We present our technique how to tune the Capture Step Framework and explain our modifications and difficulties. Afterwards we demonstrate how to compensate grasped objects and prove the effectiveness with experiments. iii

Item Type: Master Thesis
Erschienen: 2016
Creators: Reimold, Florian
Title: Robust Locomotion of a Humanoid Robot Considering Grasped Objects
Language: English
Abstract:

During the DARPA Robotics Challenge (DRC) in 2015, robots had to solve tasks in a disaster scenario motivated by the Fukushima nuclear incident. The robots had to be able to operate in an environment, which was designed for humans. This encouraged the development of humanoid-shaped robots. One task was to use a battery-powered drill to cut a hole in a wall. During the DRC, those tools were located right next to the wall, but in real world scenarios, it cannot be assumed to find the proper tool directly next to the place where it is needed. In most cases, the robot has to carry a tool across the site to complete the task. Therefore, a humanoid robot must be able to carry a needed tool without falling down. In this thesis, we investigate an approach how to enable a THOR-MANG robot to walk and carry objects without falling. We applied different walking approaches and finally decided to extend Missura’s Capture Step Framework to enable the robot to carry tools. We present our technique how to tune the Capture Step Framework and explain our modifications and difficulties. Afterwards we demonstrate how to compensate grasped objects and prove the effectiveness with experiments. iii

Place of Publication: Department of Computer Science (SIM)
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Date Deposited: 26 Jun 2019 07:47
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