Jian Mei gave his thesis seminar

Last Friday, MASc candidate Jian Mei presented his thesis seminar. The title of his talk was “Distributed Coverage Control of Multi-Agent System in Convective–Diffusive Time Evolving Environments”. Unfortunately, supervisor Dr. Davide Spinello was teaching a the time and couldn’t be present. Thanks for the seminar, Jian!

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Alireza Mirghasemi presented his thesis seminar

MASc candidate Seyed Alireza Mirghasemi presented his thesis seminar titled “Fractional-Order Flight Controller for Quadcopter Subjected to Ground Effect” last Friday. Supervisor Professor Dan Necsulescu was in attendance for the presentation. Congrats, Alireza!

Nathaniel Mailhot kicks things off for MCG seminars 2018-2019!

Welcome back to everyone for another academic year of MCG seminars! It was good to see such a full house on our first day.

To kick things off for the semester, MASc candidate Nathaniel Mailhot presented his thesis seminar titled “Pupil Tracking and Control of a Laser Based Power System for a Vision Restoring Retinal Implant”. A really interesting talk! Supervisor Dr. Spinello was also present for the seminar and photo-op. Congrats, Nathaniel!

Jasmeet Singh Ladoiye presented his MASc thesis seminar

For the last seminar of winter 2018, Jasmeet Singh Ladoiye presented his MASc work at our MCG seminar series. Jasmeet’s talk was titled “control of surgical robot using model predictive control with time delay”. Unfortunately neither thesis supervisor (Drs. Dan Necsulescu and Jurek Sasiadek) could be in attendance. Congratulations Jasmeet on your seminar and on getting closer to completing your MASc! Thanks to everyone that participated in this semester’s seminar series. See you next semester!

Chengming Luo presented his PhD thesis seminar

PhD candidate Chengming Luo presented his thesis seminar titled “Automatic Guidance of Agricultural Wide-Span Implement Carrier” last Tuesday. Chengming worked under the supervision of our very own former Dean, Dr. Claude Laguë.  Dr. Laguë was present for the seminar and I got the chance to take a photo of student with supervisor. Thanks for an interesting talk and congratulations to Chengming for getting close to finishing his PhD!

Last seminar of the year!

Honours of the last seminar of the year went to Adekunle Adepegba. Ade presented his thesis seminar on “Multi-Agent Area Coverage Control using Reinforcement Learning”.  Supervisor Dr. Davide Spinello was in attendance.  

Congrats to everyone who presented a seminar this year and thanks to everyone who participated. I hope everyone has a great and restful holiday season and here’s to seeing you all in 2016!

   
 

Mostafa Fallah to present on Friday

All are cordially invited to a graduate seminar talk to be given by Mostafa Fallah.  He will give talk  titled “Coordinated Deployment of Multiple Autonomous Agents in Area Coverage Problems with Evolving Risk.”

 

Date: Friday March 20th

Time: 2:30pm

Room: CBY D207

 

Abstract

Coordinated missions with platoons of autonomous agents are rapidly becoming popular because of technological advances in computing, networking, miniaturization and combination of electromechanical systems. These multi-agents networks coordinate their actions to perform challenging spatially-distributed tasks such as search, survey, exploration, and mapping. Environmental monitoring and locational optimization are among the main applications of the emerging technology of wireless sensor networks where the optimality refers to the assignment of sub-regions to each agent, in such a way that a suitable coverage metric is maximized. Usually the coverage metric encodes a distribution of risk defined on the area, and a measure of the performance of individual robots with respect to points inside the region of interest. The risk density can be used to quantify spatial distributions of risk in the domain.

 
The solution of the optimal control problem in which the risk measures are not time varying is well known in the literature, with the optimal configuration of the robots given by the centroids of the Voronoi regions forming a centroidal Voronoi tessellation of the area. In other words, when the set of mobile robots converge to the corresponding centroids of the Voronoi tessellation dictated by the coverage metric, the coverage itself is maximized.

 
In this work, we consider a time-varying risk density function evolving according to a diffusion equation with varying boundary conditions that quantify a time-varying risk on the border of the workspace. Boundary conditions model a time varying flux of external threats coming into the area, averaged over the boundary length, so that we do not consider the individual kinematics of incoming threats but rather their averaged, distributed effect. This approach is similar to the one commonly adopted in continuum physics, in which kinematic descriptors are averaged over spatial domain and suitable continuum fields are introduced to describe their evolution. By adopting a first gradient constitutive relation between the flux and the density, we obtain a simple diffusion equation. Asymptotic convergenceand optimality of the non-autonomous system are studied by means of Barbalat’s Lemma and connections with varying boundary conditions are established. Some criteria on time-varying boundary conditions and its evolution are established to guarantee the stabilities of agents’ trajectories. A set of numerical simulations illustrate the theoretical results.

Arian Panah to present this Friday

Everyone is cordially invited to hear Arian Panah present a talk on his MASc work: “Nonuniform Coverage with Time-Varying Risk Density Function”. The abstract of the talk is attached.  The talk will start promptly at 2:30pm.

Date: Friday February 27

Time: 2:30pm

Room: CBY D207

Abstract

Multi-agent systems are extensively used in several civilian and military applications, such as surveillance, space exploration, cooperative classification, and search and rescue, to name a few. An important class of applications involves the optimal spatial distribution of a group of mobile robots on a given area, where the optimality refers to the assignment of subregions to the robots, in such a way that a suitable coverage metric is maximized. Typically the coverage metric encodes a risk distribution defined on the area, and a measure of the performance of individual robots with respect to points inside the region of interest. The risk density can be used to assign spatial distributions of risk in the region, as for example typically happens in surveillance applications in which high value units have to be protected against external threats coming into a given area surrounding them.

The solution of the optimal control problem in which the metric is autonomous (a function of time only through the state of the robots) is well known in the literature, with the optimal location of the robots given by the centroids of the Voronoi regions forming a Voronoi tessellation of the area. In other words, when the set of mobile robots configure themselves as the centroids of the Voronoi tessellation dictated by the coverage metric, the coverage itself is maximized.

In this work we advance on this result by considering a generalized area control problem in which the coverage metric is non-autonomous, that is the coverage metric is time varying independently of the states of the robots. This generalization is motivated by the study of coverage control problems in which the coordinated motion of a set of mobile robots accounts for the kinematics of objects penetrating from the outside. Asymptotic convergence and optimality of the non-autonmous system are studied by means of Barbalat’s Lemma, and connections with the kinematics of the moving intruders is established. Several numerical simulation results are used to illustrate theoretical predictions.