Paper
18 June 2015 Multi-modal sensor and HMI integration with applications in personal robotics
Rommel Alonzo, Sven Cremer, Fahad Mirza, Sandesh Gowda, Larry Mastromoro, Dan O. Popa
Author Affiliations +
Abstract

In recent years, advancements in computer vision, motion planning, task-oriented algorithms, and the availability and cost reduction of sensors, have opened the doors to affordable autonomous robots tailored to assist individual humans. One of the main tasks for a personal robot is to provide intuitive and non-intrusive assistance when requested by the user. However, some base robotic platforms can’t perform autonomous tasks or allow general users operate them due to complex controls. Most users expect a robot to have an intuitive interface that allows them to directly control the platform as well as give them access to some level of autonomous tasks. We aim to introduce this level of intuitive control and autonomous task into teleoperated robotics.

This paper proposes a simple sensor-based HMI framework in which a base teleoperated robotic platform is sensorized allowing for basic levels of autonomous tasks as well as provides a foundation for the use of new intuitive interfaces. Multiple forms of HMI’s (Human-Machine Interfaces) are presented and software architecture is proposed. As test cases for the framework, manipulation experiments were performed on a sensorized KUKA YouBot® platform, mobility experiments were performed on a LABO-3 Neptune platform and Nexus 10 tablet was used with multiple users in order to examine the robots ability to adapt to its environment and to its user.

© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rommel Alonzo, Sven Cremer, Fahad Mirza, Sandesh Gowda, Larry Mastromoro, and Dan O. Popa "Multi-modal sensor and HMI integration with applications in personal robotics", Proc. SPIE 9494, Next-Generation Robotics II; and Machine Intelligence and Bio-inspired Computation: Theory and Applications IX, 949409 (18 June 2015); https://doi.org/10.1117/12.2177641
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Robots

Robotics

Control systems

Human-machine interfaces

Neptune

Tablets

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