Collision detection, isolation and identification for humanoids

Publikation: Sonstige PublikationForschungPeer-Review

Autoren

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seitenumfang8
ISBN (elektronisch)9781509046331
PublikationsstatusVeröffentlicht - Mai 2017

Abstract

High-performance collision handling, which is divided into the five phases detection, isolation, estimation, classification and reaction, is a fundamental robot capability for safe and sensitive operation/interaction in unknown environments. For complex humanoid robots collision handling is obviously significantly more complex than for classical static manipulators. In particular, the robot stability during the collision reaction phase has to be carefully designed and relies on high fidelity contact information that is generated during the first three phases. In this paper, a unified realtime algorithm is presented for determining unknown contact forces and contact locations for humanoid robots based on proprioceptive sensing only, i.e. joint position, velocity and torque, as well as force/torque sensing along the structure. The proposed scheme is based on nonlinear model-based momentum observers that are able to recover the unknown contact forces and the respective locations. The dynamic loads acting on internal force/torque sensors are also corrected based on a novel nonlinear compensator. The theoretical capabilities of the presented methods are evaluated in simulation with the Atlas robot. In summary, we propose a full solution to the problem of collision detection, collision isolation and collision identification for the general class of humanoid robots.

ASJC Scopus Sachgebiete

Zitieren

Collision detection, isolation and identification for humanoids. / Vorndamme, Jonathan; Schappler, Moritz; Haddadin, Sami.
8 S. 2017.

Publikation: Sonstige PublikationForschungPeer-Review

Vorndamme J, Schappler M, Haddadin S. Collision detection, isolation and identification for humanoids. 2017. 8 S. doi: 10.1109/icra.2017.7989552
Download
@misc{4242600c2a0c49a59f999e1312e6c056,
title = "Collision detection, isolation and identification for humanoids",
abstract = "High-performance collision handling, which is divided into the five phases detection, isolation, estimation, classification and reaction, is a fundamental robot capability for safe and sensitive operation/interaction in unknown environments. For complex humanoid robots collision handling is obviously significantly more complex than for classical static manipulators. In particular, the robot stability during the collision reaction phase has to be carefully designed and relies on high fidelity contact information that is generated during the first three phases. In this paper, a unified realtime algorithm is presented for determining unknown contact forces and contact locations for humanoid robots based on proprioceptive sensing only, i.e. joint position, velocity and torque, as well as force/torque sensing along the structure. The proposed scheme is based on nonlinear model-based momentum observers that are able to recover the unknown contact forces and the respective locations. The dynamic loads acting on internal force/torque sensors are also corrected based on a novel nonlinear compensator. The theoretical capabilities of the presented methods are evaluated in simulation with the Atlas robot. In summary, we propose a full solution to the problem of collision detection, collision isolation and collision identification for the general class of humanoid robots.",
author = "Jonathan Vorndamme and Moritz Schappler and Sami Haddadin",
note = "Funding information: niz1Universit{\"a}t Hannover, lastname@irt.uni-hannover.de. This work has been partially funded by the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 688857 (“SoftPro”) and by the Alfried-Krupp Award for young professors.",
year = "2017",
month = may,
doi = "10.1109/icra.2017.7989552",
language = "English",
type = "Other",

}

Download

TY - GEN

T1 - Collision detection, isolation and identification for humanoids

AU - Vorndamme, Jonathan

AU - Schappler, Moritz

AU - Haddadin, Sami

N1 - Funding information: niz1Universität Hannover, lastname@irt.uni-hannover.de. This work has been partially funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688857 (“SoftPro”) and by the Alfried-Krupp Award for young professors.

PY - 2017/5

Y1 - 2017/5

N2 - High-performance collision handling, which is divided into the five phases detection, isolation, estimation, classification and reaction, is a fundamental robot capability for safe and sensitive operation/interaction in unknown environments. For complex humanoid robots collision handling is obviously significantly more complex than for classical static manipulators. In particular, the robot stability during the collision reaction phase has to be carefully designed and relies on high fidelity contact information that is generated during the first three phases. In this paper, a unified realtime algorithm is presented for determining unknown contact forces and contact locations for humanoid robots based on proprioceptive sensing only, i.e. joint position, velocity and torque, as well as force/torque sensing along the structure. The proposed scheme is based on nonlinear model-based momentum observers that are able to recover the unknown contact forces and the respective locations. The dynamic loads acting on internal force/torque sensors are also corrected based on a novel nonlinear compensator. The theoretical capabilities of the presented methods are evaluated in simulation with the Atlas robot. In summary, we propose a full solution to the problem of collision detection, collision isolation and collision identification for the general class of humanoid robots.

AB - High-performance collision handling, which is divided into the five phases detection, isolation, estimation, classification and reaction, is a fundamental robot capability for safe and sensitive operation/interaction in unknown environments. For complex humanoid robots collision handling is obviously significantly more complex than for classical static manipulators. In particular, the robot stability during the collision reaction phase has to be carefully designed and relies on high fidelity contact information that is generated during the first three phases. In this paper, a unified realtime algorithm is presented for determining unknown contact forces and contact locations for humanoid robots based on proprioceptive sensing only, i.e. joint position, velocity and torque, as well as force/torque sensing along the structure. The proposed scheme is based on nonlinear model-based momentum observers that are able to recover the unknown contact forces and the respective locations. The dynamic loads acting on internal force/torque sensors are also corrected based on a novel nonlinear compensator. The theoretical capabilities of the presented methods are evaluated in simulation with the Atlas robot. In summary, we propose a full solution to the problem of collision detection, collision isolation and collision identification for the general class of humanoid robots.

UR - http://www.scopus.com/inward/record.url?scp=85027992648&partnerID=8YFLogxK

U2 - 10.1109/icra.2017.7989552

DO - 10.1109/icra.2017.7989552

M3 - Other publication

ER -

Von denselben Autoren