Abstract
Most of the original image feature detectors are not able to cope with large photometric variations, and their extensions that should improve detection eventually increase the computational cost and introduce more noise to the system. Here we extend the original SURF algorithm increasing its invariance to illumination changes. Our approach uses the local space average color descriptor as working space to detect invariant features. A theoretical analysis demonstrates the impact of distinct photometric variations on the response of blob-like features detected with the SURF algorithm. Experimental results demonstrate the effectiveness of the approach in several illumination conditions including the presence of two or more distinct light sources, variations in color, in offset and scale.

Abstract
Intelligent wheelchairs can become an important solution to assist physically impaired individuals who find it difficult or impossible to drive regular powered wheelchairs. However, when designing the hardware architecture several projects compromise the user comfort and the wheelchair normal usability in order to solve robotic problems. In this paper we describe the main concepts regarding the design of the IntellWheels intelligent wheelchair. Our approach has a user-centered perspective, in which the needs and limitations of physically impaired users are given extensive attention at each stage of the design process. Finally, our design was evaluated through a public opinion assessment. A statistical analysis suggested that the design was effective to mitigate the visual and ergonomic impacts caused by the addition of sensorial and processing capabilities on the wheelchair. © 2013 IEEE.

Abstract
Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach.

Abstract
Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions. © Springer International Publishing Switzerland 2017.

Abstract
Control applications are a key aspect of current industrial environments. Regarding cork industries, there is a particular process that needs to be addressed: the cork stoppers drying. Currently the methodology used in this process delays the overall production cycle and lacks in the drying efficiency itself. This paper presents the development of a cork stopper drying system based on the control of a conveyor based machine using Model Predictive Control (MPC). Throughout the project itwas also developed a drying kineticsmodel for the cork stoppers and an extension of such model to a discrete space state model. By applying the proposed methodology it is assured the cork stoppers’ drying in a faster and more efficient way. © Springer International Publishing Switzerland 2017.

Abstract
A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. At the same time, simulation has becoming more and more used in industries and academia since it presents several advantages. It takes the building and rebuilding phase out of the loop by using the model already created in the design phase. Further, simulation time on testing is cheaper and faster than performing the multiple tests of the design each time. Besides, it is easier to measure some variables in simulation than in real scenarios. In this paper, a laser scanner sensor is modeled and implemented in a developed simulator that already has several other sensors and actuators models. The presented simulation reflects the laser model properties such as target color dependences, noise, limits, time constraints, and target angle functions. As a case study, the same scenario is assembled with real components on a conveyer belt and in simulation. Results from both approaches are compared and validate the proposed model methodology. As an example, a 3D object recognition task is addressed highlighting the developed realistic model. Further industrial and R&D implementations based on this sensor could be stressed in simulation before implementation. © Springer International Publishing Switzerland 2013.