Robot Button Pressing in Human Environments @ICRA-cg8kk

Uploaded May 2018 | Updated September 2026, 2 weeks ago

ICRA 2018 Spotlight Video
Interactive Session Thu PM Pod K.1
Authors: Wang, Fan; Chen, Gerry; Hauser, Kris
Title: Robot Button Pressing in Human Environments

Abstract:
Service robots will need to actuate buttons and switches designed for humans in order to conduct many desirable functions. This paper presents the design of a robot named SwitchIt that is small, relatively inexpensive, easily mounted on a mobile robot, and actuates buttons reliably. Its operating characteristics were developed after conducting a systematic study of buttons and switches in human environments. From this study, we develop a categorization of buttons based on a sets of physical properties relevant for robots to operate them. After a human calibrates and annotates buttons in the robot's environment using a hand-held tablet, the system automatically recognizes, pushes, and detects the state of a variety of buttons. Empirical tests demonstrate that the system succeeds in operating 95.7% of 234 total buttons/switches in an office building and a household environment.

Robot Button Pressing in Human Environments

$Decentralized Adaptive Control for Collaborative Manipulation ICRA 2018 Spotlight Video Interactive Session Tue AM Pod F.1 Authors: Culbertson, Preston; Schwager, Mac Title: Decentralized Adaptive Control for Collaborative Manipulation Abstract: This paper presents a design for a decentralized adaptive controller that allows a team of agents to manipulate a common payload in {R}^2$ or {R}^3$. The controller requires no communication between agents and requires no textit{a priori} knowledge of agent positions or payload properties. The agents can control the payload to track a reference trajectory in linear and angular velocity with center-of-mass measurements, in angular velocity using only local measurements and a common frame, and can stabilize its rotation with only local measurements. The controller is designed via a Lyapunov-style analysis and has proven stability and convergence. The controller is validated in simulation and experimentally with four robots manipulating an object in the plane.$

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