Efficient Mission Planning for Mobile Robot Networks in Communication Constrained Environment

Speaker Bio

Md Mahbubur Rahman is a Ph.D candidate in the School of Computing and Information Sciences at FIU under the supervision of Dr. Leonardo Bobadilla.  His research interest includes robotics, motion planning, intelligent system design and task automation. He has published his works in premier robotic conferences such as IEEE ICRA, IEEE CASE, IEEE MILCOM. Mahbub has completed his Bachelors from BUET, Bangladesh and Masters from FIU.  He also held several industrial positions in Bangladesh and successfully completed an internship opportunity in Harrisburg, PA, USA.

Description

The use of networked autonomous vehicles has an increasing demand for many risky and labor intensive tasks such as military missions, search and rescue operations, construction automation, and environmental monitoring. One potential weakness of autonomous network systems is that communication among the autonomous vehicles can be interrupted and degraded by many factors, including random movements, out of range locations, physical obstructions, atmospheric conditions, electromagnetic interference, and adversarial attacks (e.g. jamming and sniffing). In this thesis, we propose three-pronged approaches to alleviate some of these issues: 1) Communication aware planning algorithms in autonomous system networks; 2) Communication connectivity maintenance using the Line-of-Sight (LoS); and 3) Communication aware world models for navigation.

First, we focus on quantifying the safety score of a fully automated robotic mission where the coexistence of human and robot is required without any collision risk. A number of alternate mission plans are analyzed using motion planning algorithms to select the safest one. Furthermore, an efficient multi-objective optimization based path planning for the robots is developed to deal with several Pareto optimal cost attributes.

Second, in communication denied environments, we use Line-of-Sight (LoS) to establish communication 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.

Finally, we develop a communication aware world map that integrates traditional world models with the robotic motion plans where one or multiple mobile units need to be controlled by a remote operator with the help of a number of intermediate relay robots. Our proposed communication map selects the optimal placement of a chain of relay vehicles in order to maximize communication quality.