Absolute joint-angle estimation of Generalised N-Trailer vehicles equipped with incremental encoders using moving horizon estimation.

The Generalised N-Trailer (GNT) vehicle is a tool for field operations that optimises harvesting and transportation tasks, offering a highly scalable payload using only one tractor. Precise knowledge of the position and attitude of each segment in the chained vehicle is crucial for the controller's success during operation. In this study, we propose the use of a Nonlinear Moving Horizon Estimator (NMHE) to estimate the system's state when the GNT vehicle is equipped with incremental encoders on its joints.

Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions.

Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early.

Retrieval of Vegetation Indices Related to Leaf Water Content from a Single Index: A Case Study of (Labill.) and (D. Don.).

The vegetation indices derived from spectral reflectance have served as an indicator of vegetation's biophysical and biochemical parameters. Some of these indices are capable of characterizing more than one parameter at a time. This study examines the feasibility of retrieving several spectral vegetation indices from a single index under the assumption that all these indices are correlated with water content.

Machine learning for computer-aided polyp detection using wavelets and content-based image.

The continuous growing of machine learning techniques, their capabilities improvements and the availability of data being continuously collected, recorded and updated, can enhance diagnosis stages by making it faster and more accurate than human diagnosis. In lower endoscopies procedures, most of the diagnosis relies on the capabilities and expertise of the physician. During medical training, physicians can be benefited from the assistance of algorithms able to automatically detect polyps, thus enhancing their diagnosis.

Human-inspired sound environment recognition system for assistive vehicles.

Objective: The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars.

Towards a new modality-independent interface for a robotic wheelchair.

This work presents the development of a robotic wheelchair that can be commanded by users in a supervised way or by a fully automatic unsupervised navigation system. It provides flexibility to choose different modalities to command the wheelchair, in addition to be suitable for people with different levels of disabilities. Users can command the wheelchair based on their eye blinks, eye movements, head movements, by sip-and-puff and through brain signals.

Autonomous assistance navigation for robotic wheelchairs in confined spaces.

In this work, a visual interface for the assistance of a robotic wheelchair's navigation is presented. The visual interface is developed for the navigation in confined spaces such as narrows corridors or corridor-ends. The interface performs two navigation modus: non-autonomous and autonomous.

SLAM algorithm applied to robotics assistance for navigation in unknown environments.

Background: The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals.

Human-machine interfaces based on EMG and EEG applied to robotic systems.

Background: Two different Human-Machine Interfaces (HMIs) were developed, both based on electro-biological signals. One is based on the EMG signal and the other is based on the EEG signal. Two major features of such interfaces are their relatively simple data acquisition and processing systems, which need just a few hardware and software resources, so that they are, computationally and financially speaking, low cost solutions.