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Control and automation has gone through tremendous developments for the past few decades. After briefly reviewing the history of control this talk will present some Magnus challenges to control. In particular, this talk will take model based fuzzy control as an example to share a personal perspective on developments and challenges in this chosen topic.
Considering that energy use in buildings represents more than 40% of global energy consumption and that humans spend 90% of the time indoors, technologies enabling smarter buildings can lead to significant reductions in greenhouse gas emissions, and produce a comfortable, efficient and sustainable environment. This is to be achieved through smart sensing, advanced automation, and intelligent computing/communication...
Recent advances in robot technologies coupled with the growing economic competitiveness of robots in the workplace vis-a-vis human workers has spurred a renewed interest in robotic manufacturing. Major national research and development initiatives in robotics and manufacturing are underway in many countries, and several manufacturers have released commercial prototypes of dual-arm and other advanced...
Advances in microelectronics and communication technologies make networked sensing and control feasible. Well known examples include mobile sensor networks for environment monitoring, unmanned aircraft in search and rescue operations, arrays of micro satellites that form a distributed large aperture radar, and vehicle platooning in intelligent transportation systems. The distributed nature of information...
Unmanned aerial vehicles (UAVs) have made huge progress in military and civilian missions, ranging from surveillance, reconnaissance, to logistics and transportation. Particularly, to meet requirements of high-demand applications, it is necessary to develop advanced unmanned systems that are capable of autonomously navigating in cluttered indoor and outdoor GPS-denied environments, such as hostile...
Canada holds oil reserve at 168 billion barrels — in the form of oil sands in the Province of Alberta-ranking it the third largest in the world. In this lecture, I will highlight our collaborative research with Canadian oil sands producers — in computer vision, image processing and machine learning — to address some of the challenges facing this important Canadian industry. Specifically I will provide...
As physical objects connect over information-exchange networks, new abstractions and design tools are needed. This is particularly true when the physical objects move and act in the world, e.g., robots. We will discuss some of the fundamental challenges and opportunities that present themselves when robots connect on a large scale, taking us from an internet with things, to an Internet of Things.
The last few years have seen significant progress in our understanding of how one should structure multi-robot systems. New control, coordination, and communication strategies have emerged and, in this talk, we discuss some of these developments. In particular, we will show how one can go from global, geometric, team-level specifications to local coordination rules for achieving and maintaining formations,...
We propose some basic elements of a robot motor control system that have direct counterparts in human motor control, based on the premise that optimality is the fundamental principle underlying both human and robot motor control. We first review some of the basic principles and hypotheses from human motor control, particularly those mechanisms for coping with the degrees of freedom problem, and the...
Visual Simultaneous Localisation and Mapping is the process whereby a camera builds a map of a previously unseen environment, and localises itself with respect to that environment, often in real-time. Although there has been remarkable progress, and it is now possible, for example, to build dense maps in real-time using high-end commodity hardware, most SLAM research has remained rooted in geometry...
Systems and Control is now a mature subject with a deep mathematical theory and a powerful engineering methodology; its roots lie in antiquity but it emerged in the form of the Watt governor more than two centuries ago as an enabling technology of the Industrial Revolution, and its development since then involves critical contributions in a broad range of domains stretching from the Space Race to...
Modern cars include more and more sophisticated electronics, sensors, processing and control components. These new components are used both for controlling the main functions of the vehicle and for providing the driver with Advanced Driving Assistance Systems (ADAS). Such ADAS functionalities are increasingly based on Robotics technologies for partly automating some driving functions such as adaptive...
The trend of integrating power systems with advanced computer and communication technologies has introduced serious cyber security concerns, especially in a smart grid environment where the cyber system is no longer regarded as 100% reliable to support power system communications and control as before. Power system security therefore extends to potential cyber security domain in the smart grid era...
Steady-state visual evoked potentials (SSVEPs) enable brain-computer interfaces to achieve efficient performance in command detection accuracy and information transfer rate (ITR). However, a limited bandwidth of SSVEPs causes a limited number of possible command in BCIs. Moreover since the amplitude of SSVEP at a particular frequency depends on users, some BCI commands could be executed easily (higher...
This paper presents a power-efficient VLSI implementation of a feature extraction engine for the applications of real-time spike sorting. Traditional method like principal components analysis (PCA) works in a batch mode by diagonalizing the covariance matrix constructed from the whole bunch of input data, which is computationally prohibitive and does not favor real-time processing. The proposed hardware...
This paper is aimed to predict pain perception from laser-evoked EEG oscillatory activities in the time-frequency domain with multivariate pattern analysis (MVPA). We first identify pre-/post-stimulus EEG oscillatory activities that are correlated with the intensity of laser-evoked pain perception using a multivariate linear regression (MVLR) model, which is solved by partial least-squares regression...
Attention Deficiency Hyperactivity Disorder (ADHD) as a disruptive behavior disorder is receiving lots of attention because of its complexity and need for early detection. This paper presents a study on identification of potential biomarkers in the diagnosis of ADHD based on the structural-MRI of the brain obtained through ADHD-200 competition data set. The region of the brain considered here is "hippocampus"...
The neuro engineering research over the past decades has established Electroencephalography based Brain Computer Interface (EEG-BCI) systems as an efficient means of decoding brain activity. Motor control BCI is a category of BCI that analyzes neural activity recorded over sensory motor area to classify or decode intended motor tasks. For a BCI system, it is desired to have defined and independent...
An effective speech brain machine interface requires selecting the best cortical recording sites and signal features for decoding speech production, but also minimal clinical risk for the patient. Motivated by this need to reduce patient risk, the purpose of this study is to detect voice activity (speech onset and offset) automatically from spatial-spectral features of electrocorticographic signals...
In this paper we describe a new technique for segment meaningfully objects autonomously. Traditional segmentation scheme tries to find the best segmentation result at some trade off between level of user input and level of meaningful segmentation. Segmentation with user input will ensure better segmentation result but is not applicable to the realtime autonomous robotics system. For most of the commercial...
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