PGRs meeting and Research Presentations – June 2015

The monthly PGRs Research Presentations was held on Wed.  10th June, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Effects of Environmental Changes on Aggregation with Robot Swarm“. Title:   “Computer-aided Liver lesion detection and classification

By: Farshad Arvin

By: Hussein Alahmer

Abstract: Aggregation is one of the most fundamental behaviors that has been studied in swarm robotic researches for more than two decades. The studies in biology revealed that environment is a very important factor especially in cue-based aggregation in which a heterogeneity in the environment such as a heat or light source act as a cue indicating an optimal aggregation zone. In swarm robotics, studies on cue-based aggregation mainly focused on different methods of aggregation and different parameters such as population size. Although of utmost importance, effects of environmental factors have not been studied extensively. In this work, we study the effect of different  environmental factors such as size and texture of aggregation cues and speed of the changes on a dynamic environment using real robots. We used aggregation time and size of the aggregate as the two metrics and evaluated the performance of the swarm aggregation in static and dynamic environments. The results of the performed experiments illustrate how environmental changes influence the performance of a swarm aggregation.

AbstractLiver cancer is one of the major death factors in the world. Transplantation and tumor resection are two main therapies in common clinical practice. Both tasks need image assisted planning and quantitative evaluations. An efficient and effective automatic liver segmentation is required for corresponding quantitative evaluations. Computed Tomography (CT) is highly accurate for liver cancer diagnosis. Manual identification of hepatic lesions done by trained physicians is a time-consuming task and can be subjective depending on the skill, expertise and experience of the physician.

Computer aided classification of liver tumors from abdominal Computer Tomography (CT) images requires segmentation and analysis of tumor. Automatic segmentation of tumor from CT images is difficult, due to the size, shape, position and presence of other objects with the same intensity present in the image.

The proposed system automatically segment liver from abdominal CT and detect hepatic lesions, then classifies the lesion into Benign or Malignant. The method uses Fuzzy C Means (FCM) clustering and region growing technique. The effectiveness of the algorithm is evaluated by comparing automatic segmentation results to the manual segmentation results. Quantitative comparison shows a close correlation between the automatic and manual as well as high spatial overlap between the regions-of-interest (ROIs) generated by expert radiologist and proposed system.






PGRs meeting and Research Presentations – March 2015

The monthly PGRs Research Presentations was held on Wed. 11th March, 2pm, Room MC3108.

This session we had the following presentations:

Title: “Retinal Vascular Measurement“. Title:   “4D Lifelong Exploration of Dynamic Environments

By: Francesco Caliva

By: Joao Santos

Abstract: Several studies have shown that systemic diseases affect blood vessels’ geometry. Retina is a window in the vascular system, thus fundus images can be adopted to diagnose or evaluate pathological conditions. Segmentation algorithms are not able to completely segment blood vessels. This failure results in a set of disconnected vascular segments. Reconstructing the whole network has crucial importance. At this aim, in this work, implicit neural cost functions have been adopted to evaluate how the segments can be joined. In this talk I will present my current and future work. Abstract:  We present a novel 4D lifelong exploration method for dynamic, human populated environments. In contrast to other exploration methods that model the environment as being static, our spatio-temporal exploration method creates and maintains a world model that not only represents the environment’s 3D structure, but also its dynamics over time.The predictive ability of the 4D spatio-temporal model allows the exploration method not only where, but also when to make environment observations.
To validate our method, a mobile robot was deployed over 5 days in an office environment, and the proposed method was compared against a static approach. The results show that through understanding of the environment dynamics, the spatio-temporal exploration algorithm could predict which locations were going to change at a specific time and used this knowledge to guide the robot. This allowed our spatio-temporal exploration method to gather more information that the exploration method that relied on a static environment model.






PGRs Research Presentations – November 2013

The monthly PGRs Research Presentations was held on Wed. 13th November, 2pm, Room MC0025 (Ground floor).

This session we had the following presentations:

Title: “Shaping human-aware navigation and human-robot joint motion using long-term adaptation“. Title:   “Data Analysis of Agent-based Crowd Simultion

By: Christian Dondrup

By: Qinbing Fu

Abstract:Enabling a mobile service robot to move in a human populated environment is not only a question of safety but also of predictability, consistency, team work efficiency, and the general feeling of comfort of the human. This leads to a form of human-robot joint motion and human-aware navigation which is supposed to be most pleasant for the people involved. There are currently many approaches of solving this issue but most of them are built on constraints and static learning methods and not on long-term learning through interaction. The main focus of this thesis is therefore the creation of novel approaches to shape a robots spatial behaviour ”on-the-fly” using long-term experiences from engagements in joint movements with lay users and trying to find and understand adaptation needs and thereby create a predictable, readable and consistent robot behaviour.This first presentation will focus on state-of-the-art methods of social and human-aware navigation and a first study conducted to find gestures indicating adaptation needs to improve the feeling of comfort of human interaction partners and the likabilaty of the robot itself. Abstract: This work is based on clustering and visualizing an agent-based crowd simulation data in an airport, using K-means, Gaussian Mixture Model and Hidden Markov Model. With the help of these models, we mainly aim to verify the feasibility of our approach to analyse agents’ behaviour in the airport.




The meeting started by welcoming the new PGRs arrived.

After presentations and Q/A sessions, the meeting continued with:

* Congratulations Talal Al-Bacha, for his new baby girl.

* Brief information on the “Students Representative” duties/responsibilities/benefits.

* Election of the PGRs Students Representatives: 2 nominations and 2 positions available (based on a Rep for each 25 PGR).

* Students Reps for this academic year are: Christian Dondrup  and  Touseef Qureshi.

* Discussion about potential activities (social, trips,…etc.)