Human-Multirobot Collaborative Mobile Manipulation: the Omnid Mocobots

The Omnid human-collaborative mobile manipulators are an experimental platform for testing control architectures for autonomous and human-collaborative multirobot mobile manipulation. An Omnid consists of a mecanum-wheel omnidirectional mobile base and a series-elastic Delta-type parallel manipulator, and it is a specific implementation of a broader class of mobile collaborative robots ("mocobots") suitable for safe human co-manipulation of delicate, flexible, and articulated payloads. Key features of mocobots include passive compliance, for the safety of the human and the payload, and high-fidelity end-effector force control independent of the potentially imprecise motions of the mobile base. We describe general considerations for the design of teams of mocobots; the design of the Omnids in light of these considerations; manipulator and mobile base controllers to achieve useful multirobot collaborative behaviors; and initial experiments in human-multirobot collaborative mobile manipulation of large, unwieldy payloads. For these experiments, the only communication among the humans and Omnids is mechanical, through the payload.Comment: 8 pages, 10 figures. Videos available at https://www.youtube.com/watch?v=SEuFfONryL0. Submitted to IEEE Robotics and Automation Letters (RA-L

The Interface Usage Skills Test: An Open Source Tool for Quantitative Evaluation in Real Time for Clinicians and Researchers

Assistive machines endow people with limited mobility the opportunity to live more independently. However, operating these machines poses risks to the safety of the human operator as well as the surrounding environment. Thus, proper user training is an essential step towards independent control and use of functionally assistive machines. The human operator can use a variety of control interfaces to issue control signals to the device, depending on the residual mobility and level of injury of the human operator. Proficiency in operating the interface of choice precedes the skill in operating the assistive machine. In this systems paper, we present an open source tool for automatically and objectively quantifying user skill in operating various interface devices.Comment: 6 pages, 4 figures, accepted at ICORR 202