Multi-modal Proactive Approaching of Humans for Human-Robot Cooperative Tasks

Author(s):  
Lakshadeep Naik ◽  
Oskar Palinko ◽  
Leon Bodenhagen ◽  
Norbert Kruger
Keyword(s):  
Author(s):  
Hirohisa Hirukawa

The Humanoid Robotics Project of the Ministry of Economy, Trade and Industry of Japan realized that biped humanoid robots can perform manual labour. The project developed humanoid robot platforms, consisting of humanoid robot hardware and a package of fundamental software, and explored applications of humanoid robots on them. The applications include maintenance tasks of industrial plants, teleoperation of industrial vehicles, cooperative tasks with a human, guarding the home and office and the care of patients in beds.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Paul Ibbotson ◽  
Christoph Hauert ◽  
Richard Walker

AbstractRecent research on the conditions that facilitate cooperation is limited by a factor that has yet to be established: the accuracy of effort perception. Accuracy matters because the fitness of cooperative strategies depends not just on being able to perceive others’ effort but to perceive their true effort. In an experiment using a novel effort-tracker methodology, we calculate the accuracy of human effort perceptions and show that accuracy is boosted by more absolute effort (regardless of relative effort) and when cooperating with a “slacker” rather than an “altruist”. A formal model shows how such an effort-prober strategy is likely to be an adaptive solution because it gives would-be collaborators information on when to abort ventures that are not in their interest and opt for ones that are. This serves as a precautionary measure against systematic exploitation by extortionist strategies and a descent into uncooperativeness. As such, it is likely that humans have a bias to minimize mistakes in effort perception that would commit them to a disadvantageous effort-reward relationship. Overall we find support for the idea that humans have evolved smart effort detection systems that are made more accurate by those contexts most relevant for cooperative tasks.


2001 ◽  
Author(s):  
Paul S. Schenker ◽  
Terrance L. Huntsberger ◽  
Paolo Pirjanian ◽  
Eric T. Baumgartner ◽  
Hrand Aghazarian ◽  
...  

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