Md Mahbubur Rahman
Florida International University
Md Mahbubur Rahman is currently a Ph.D. candidate at FIU’s School of Computing and Information Sciences. He received a master’s degree in computer science from the School of Computing and Information Sciences in Spring 2015. His major professor is Dr. Leonardo Bobadilla under whom he has completed several research projects focusing on robotics, autonomous systems, safety optimization, vehicle navigation, and multi-robot formation. He has published in the top-ranked journal (T-ASE) and conferences (ICRA, CASE, MILCOM) and most of his work are funded by the Army Research Office and FIU’s University Graduate School. He also holds a U.S. patent for his work on hair transplantation robot.
Many robotic systems are remotely operated nowadays that require uninterrupted connection and safe mission planning. Such systems are commonly found in military drones, search and rescue operations, mining robotics, agriculture, and environmental monitoring. Different robotic systems may employ disparate communication modalities such as radio network, visible light communication, satellite, infrared, Wi-Fi. However, in an autonomous mission where the robots are expected to be interconnected, communication constrained environments frequently arise due to the out of range problem or unavailability of signal. Furthermore, several automated projects (building construction, assembly line) do not guarantee uninterrupted communication, and a safe project plan is required that optimizes collision risks, cost, and duration. In this thesis, we propose four pronged approaches to alleviate some of these issues.
First, we focus on developing a communication aware world map that integrates traditional world models with the planning of multi-robot placement. Our proposed communication map selects the optimal placement of a chain of intermediate relay vehicles in order to maximize communication quality to a remote unit. Second, in communication denied environments, we use Line-of-Sight (LoS) to establish connectivity between mobile robots, control their movements and relay information to other autonomous units. We formulate and study the complexity of a multi-robot relay network positioning problem and propose approximation algorithms that restore visibility based connectivity through the relocation of one or more robots. Third, we develop a framework to quantify the safety score of a fully automated robotic project (e.g. building construction) where the coexistence of human and robot may pose collision risks. A number of alternate project plans are analyzed using motion planning algorithms to select the safest one. Finally, an efficient multi-objective optimization based robotic path planning algorithm is proposed to deal with different cost attributes and several Pareto optimal solutions.