Simulation Training to Work with Bridge Inspection Robots (WD-3)

Lead University:

University of Nevada, Reno

Principal Investigator:

Dr. Sushil Louis, University of Nevada, Reno (UNR)

PI Contact Information:

Phone: (775) 784-4315  |  Email:

Funding Sources and Amounts Provided:

UNR: $37,320

INSPIRE UTC: $37,320

Total Project Cost: $74,640

Match Agencies ID or Contract Number:

UNR: In-kind Match | INSPIRE UTC: 00055082-04D

INSPIRE Grant Award Number: 69A3551747126

Start Date: January 1, 2020
End Date: August 30, 2021

Brief Description of Research Project:

Bridge inspection is a human and capital resource intensive process critical to human safety and long term economic health. The PI proposes to investigate and develop software to train human operators in monitoring and controlling a team of steel truss bridge inspection robots that will significantly decrease inspection cost, increase inspection reliability, and improve bridge safety. A single trained operator can control multiple robots. The software system being proposed thus enables a single person to control multiple heterogeneous inspection robots being investigated and developed under other INSPIRE UTC projects. Fewer expensive human operators reduced costs while multiple robots inspecting in parallel reduces time. Our proposed system thus trains human workforce operators to directly meet the INSPIRE UTC goal of making inspection and maintenance more reliable and cost-effective.

Approach and Methodology: The same system and command interfaces are being used for training human bridge operators in simulation and in an operational environment. We propose a three-step process. First, map the simulated world to the real world. Second, connect simulated robots with real robots being developed in other INSPIRE projects, and third, investigate and develop algorithms, protocols, and autonomy for maximizing inspection speed and completeness for human-robot bridge inspection teams on real-world sized bridges. We thus expect a straightforward transition from simulation training to on-site operation as the DOT moves to leverage our system’s AI and autonomy development to increase safety and reduce cost.

Overall Objectives: This project aims to further develop a Real-Time Robot command System (RTRS). This prototype control and simulation system will feature automated route generation, connectivity to at least two types of robots, and enable multiple views of robots’ task achieving progress. RTRS will be publicly available on Github and on the INSPIRE site.

Scope of Work in Year 1: (1) Investigate algorithms for simulation control and mapping of multiple inspection robots within the same software system, (2) Integrate routing optimization into the simulation system to reduce human operator fatigue and improve monitoring, and (3) Evaluate inspection performance under different constraints.

Scope of Work in Year 2: (1) Extend to at teams composed from at least two types of inspection robots, (2) Scale robot routing to real-world large truss bridges, and (3) Demonstrate and evaluate software usability and effectiveness with Inspire developed robots.

Implementation of Research Outcomes:
Research outcomes and implementation plan will be described towards the end of this project.

Impacts/Benefits of Implementation: 
Impact/benefits of implementation will be summarized at the end of this project.

Project Website:

Progress Reports: