Collaborative Modular Robot Teammates for Shipboard Inspection and Maintenance
Abstract
Inspection, maintenance and emergency response are three of the most important shipboard tasks since vessels provide human living on a fuel storage farm and a power plant with high voltage. Vessels are structured complicatedly and equipped with numerous devices and tools. Many inspection and maintenance tasks are currently conducted by humans, so it is imperative that these tasks be automated for the maximization of safety and the minimization of workload. The fact that these tasks consist of complex human operations has given rise to need for robots which have human-like intelligent perception and flexible mobility/manipulability. The goal of this project is to develop autonomous robot teammates that perform shipboard inspection and maintenance tasks collaboratively. To achieve the goal, the technical objectives defined for the project are:~ Robots: Design and develop low-cost robots that consist of modular components and can forma variety of heterogeneous robot team; and~ Collaborative intelligence: Develop a scheme of the heterogeneous robot team that collaboratively (with intelligence) move, manipulate and complete shipboard tasks including inspection, maintenance and emergency response in shipboard environments.The robots to develop consist of modules including head, upper body, lower body, arms, legs, hands and feet/wheels. Different modules will be plugged and played to form a robot with different capabilities. The modular robot will be centrally controlled to minimize the number of electric components. Custom data/power connectors and hub will be then developed to plug and playmodules through the connection of one cable.The proposed collaborative intelligence approach is characterized by the four unique in-house technologies. The primary characteristic of the proposed approach is autonomous position/force controlled manipulation using multi-stage target observation and whole body control. To handle uncertainties of complex environments, perception implements the multi-stage probabilistic target observation technique, which maximizes the detection events while making the manipulation problem Gaussian. High-precision manipulation aimed in the project extends the multi-contact whole body control, which was proposed by the Principal Investigator (PI).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 23, 2019
- Source ID
- N000141912026
Entities
People
- Tomonari Furukawa
Organizations
- Office of Naval Research
- United States Navy
- Virginia Tech