Marnix Nuttin

Bio: Marnix Nuttin is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Mobile robot & Wheelchair. The author has an hindex of 24, co-authored 96 publications receiving 3133 citations.

Omnidirectional vision based topological navigation

Abstract: In this work we present a novel system for autonomous mobile robot navigation. With only an omnidirectional camera as sensor, this system is able to build automatically and robustly accurate topologically organised environment maps of a complex, natural environment. It can localise itself using such a map at each moment, including both at startup (kidnapped robot) or using knowledge of former localisations. The topological nature of the map is similar to the intuitive maps humans use, is memory-efficient and enables fast and simple path planning towards a specified goal. We developed a real-time visual servoing technique to steer the system along the computed path. A key technology making this all possible is the novel fast wide baseline feature matching, which yields an efficient description of the scene, with a focus on man-made environments.

Omnidirectional Vision Based Topological Navigation

Abstract: In this work we present a novel system for autonomous mobile robot navigation. With only an omnidirectional camera as sensor, this system is able to build automatically and robustly accurate topologically organised environment maps of a complex, natural environment. It can localise itself using such a map at each moment, including both at startup (kidnapped robot) or using knowledge of former localisations. The topological nature of the map is similar to the intuitive maps humans use, is memory-efficient and enables fast and simple path planning towards a specified goal. We developed a real-time visual servoing technique to steer the system along the computed path. A key technology making this all possible is the novel fast wide baseline feature matching, which yields an efficient description of the scene, with a focus on man-made environments.

Adaptive Shared Control of a Brain-Actuated Simulated Wheelchair

Abstract: The use of shared control techniques has a profound impact on the performance of a robotic assistant controlled by human brain signals. However, this shared control usually provides assistance to the user in a constant and identical manner each time. Creating an adaptive level of assistance, thereby complementing the user's capabilities at any moment, would be more appropriate. The better the user can do by himself, the less assistance he receives from the shared control system; and vice versa. In order to do this, we need to be able to detect when and in what way the user needs assistance. An appropriate assisting behaviour would then be activated for the time the user requires help, thereby adapting the level of assistance to the specific situation. This paper presents such a system, helping a brain-computer interface (BCI) subject perform goal-directed navigation of a simulated wheelchair in an adaptive manner. Whenever the subject has more difficulties in driving the wheelchair, more assistance will be given. Experimental results of two subjects show that this adaptive shared control increases the task performance. Also, it shows that a subject with a lower BCI performance has more need for extra assistance in difficult situations, such as manoeuvring in a narrow corridor.

Vibrotactile feedback for brain-computer interface operation

Abstract: To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified. In three studies with 33 subjects (including 3 with spinal cord injury), we compared vibrotactile and visual feedback, addressing: (I) the feasibility of subjects' training to master their EEG rhythms using tactile feedback; (II) the compatibility of this form of feedback in presence of a visual distracter; (III) the performance in presence of a complex visual task on the same (visual) or different (tactile) sensory channel. The stimulation protocol we developed supports a general usage of the tactors; preliminary experimentations. All studies indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training, more natural for both controls and SCI users.

Handbook of Applied Cryptography

Abstract: From the Publisher: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.

Brain-computer interfaces for communication and control

Abstract: The brain's electrical signals enable people without muscle control to physically interact with the world.

Differential Fault Analysis of Secret Key Cryptosystems

Abstract: In September 1996 Boneh, Demillo, and Lipton from Bellcore announced a new type of cryptanalytic attack which exploits computational errors to find cryptographic keys. Their attack is based on algebraic properties of modular arithmetic, and thus it is applicable only to public key cryptosystems such as RSA, and not to secret key algorithms such as the Data Encryption Standard (DES).

Brain Computer Interfaces, a Review

Abstract: A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.