PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 1, 2014123 citations

Supernumerary Robotic Limbs for aircraft fuselage assembly: Body stabilization and guidance by bracing

View Full Paper
FPFederico PariettiHAH. Harry Asada

Key Points

Key points are not available for this paper at this time.

Abstract

A new type of wearable robot that assists the wearer with extra arms secured around the hips is presented. Supernumerary Robotic Limbs (SRL) can hold objects, clamp them to a fixture, guide and support human hands, and assist the wearer in performing a task as a close co-worker. This paper focuses on a class of tasks where SRL physically interacts with the environment through contact. SRL makes contact with a wall and thereby braces the human body against the environment. SRL also guides the human hands by placing a drill jig over the drilling location. Bracing the human body and guiding the hands, SRL can enhance the drilling task stability and accuracy. The SRL technology is applied to aircraft assembly, where conventional industrial robots failed to perform effectively. First, the basic design concept of SRL is summarized, and task strategies using SRL and their functional requirements are described. Kinematic and static properties resulting from the structural closed loops formed around the SRL, the human, and the environment are analyzed, and effective strategies for physical disturbance rejection and fine positioning are discussed. A prototype robotic arm grasps the aircraft fuselage structure. Another robotic arm places a drill jig precisely on the fuselage structure, and guides and stabilizes a hand drill held by the human user. An optimization method is developed in order to identify the SRL kinematic configuration and joint torques that stabilize the drill and at the same time minimize the human workload.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Parietti et al. (2014) studied this question.

synapsesocial.com/papers/69e2ab2a579ce7f542d37b79https://doi.org/10.1109/icra.2014.6907002
Ask AI
Helpful
Bookmark
Share
View Full Paper