Fuzzy Learning Variable Admittance Control for Human-Robot Cooperation

Abstract-This paper presents a method for variable admittance control in human-robot cooperation tasks, that combines a human-like decision making process and an adaptation algorithm. A Fuzzy Inference System is designed that relies on the measured velocity and the force applied by the operator to modify on-line the damping of the robot admittance, based on expert knowledge for intuitive cooperation. A Fuzzy Model Reference Learning Controller is used to adapt the Fuzzy Inference System according to the minimum jerk trajectory model. To evaluate the performance of the proposed controller a point-to-point cooperation task is conducted with multiple subjects using a KUKA LWR robot

From Pillars to AI Technology-Based Forest Fire Protection Systems

The importance of forest environment in the perspective of the biodiversity as well as from the economic resources which forests enclose, is more than evident. Any threat posed to this critical component of the environment should be identified and attacked through the use of the most efficient available technological means. Early warning and immediate response to a fire event are critical in avoiding great environmental damages. Fire risk assessment, reliable detection and localization of fire as well as motion planning, constitute the most vital ingredients of a fire protection system. In this chapter, we review the evolution of the forest fire protection systems and emphasize on open issues and the improvements that can be achieved using artificial intelligence technology. We start our tour from the pillars which were for a long time period, the only possible method to oversee the forest fires. Then, we will proceed to the exploration of early AI systems and will end-up with nowadays systems that might receive multimodal data from satellites, optical and thermal sensors, smart phones and UAVs and use techniques that cover the spectrum from early signal processing algorithms to latest deep learning-based ones to achieving the ultimate goal

A Modified Cooperative A* Algorithm for the Simultaneous Motion of Multiple Microparts on a “Smart Platform” with Electrostatic Fields

In this article, a method for microparts parallel manipulation with electrostatic forces, applied by conductive electrodes embedded on a Programmable “Smart Platform„, is introduced. The design of the platform and the layout of the electrodes underneath the rectangular microparts with respect to the platform’s geometry are presented. The electrostatic phenomena that result to the electrostatic forces applied to the microparts by the activated electrodes of the “Smart Platform„ are studied in detail. Algorithms for the activation of the platform’s electrodes for the motion of the rectangular microparts are introduced and their motion is simulated. The Configuration-Space (C-Space) of the microparts on the “Smart Platform„ is defined taking into account the static obstacles that are placed on the platform and the rest of moving microparts. Considering the layout of the platform, the activation algorithms, the motion and the C-Space of the microparts, a modified A* algorithm is proposed and the best path for every moving rectangular micropart on the “Smart Platform„, is computed with respect to time. Simulated experiments are presented to demonstrate the effectiveness of the proposed approach and the results are discussed

Optimum Docking of an Unmanned Underwater Vehicle for High Dexterity Manipulation

A method for the determination of the optimum docking or hovering position of an Underwater Unmanned Vehicle is proposed for performing a desired intervention task with high dexterity. The optimization problem is formulated taken into account primarily the manipulator’s dexterity in the area of intervention as well as the distance between the current position and the optimal one and the geometric constraints imposed by the environment. A Genetic Algorithm is designed and implemented to search for the best docking position. An underwater scenario with a UUV equipped with a 6 DOF manipulator is examined in order to verify the applicability of the proposed approach.JRC.G.6-Digital Citizen Securit

Determination of the Optimum Docking Position for an Unmanned Underwater Vehicle using a Genetic Algorithm

Abstract: An approach for the determination of the optimum docking or hovering position of an Underwater Unmanned Vehicle is proposed towards the optimum performance for a desired intervention task. An underwater scenario with a UUV equipped with a 6 DOF manipulator is examined in order to verify the applicability of the algorithm. The optimization problem is formulated taken into account primarily the manipulator dexterity as well as the distance between the current position and the optimal one and the geometric constraints imposed by the environment. The ability of the vehicle to dock in the determined optimal location is assumed. A Genetic Algorithm is designed and implemented to search for the best docking position.JRC.DG.G.4-Maritime affair

Surface flattening based on constraint global optimization

In this paper, the problem of generating a planar development of arbitrary three-dimensional surfaces is addressed. A new method based on a global optimization process under constraints is proposed. In this method an initial planar development is derived which is refined in order to satisfy certain criteria and constraints. The refinement is formulated as a global minimization problem. Using the proposed technique it is not required to predetermine a mapping from the three-dimensional surface to the plane in order to generate the planar development and it is possible to control the local accuracy in the derived planar development. Indicative applications are presented to illustrate the effectiveness of the proposed technique

Rational Ruled surfaces construction by interpolating dual unit vectors representing lines

In this paper, a new representational model is introduced for the rational family of ruled surfaces in Computer Graphics. The surface parameterization is constructed using the NURBS basis functions and line geometry. The ruled surface is defined by interpolating directly dual unit vectors representing lines, which is a single parametric surface and its shape depends on the control lines. All the advantages of the NURBS basis such as shape control and the local modification property are also applicable and bequeathed to the dual NURBS ruled surface. The problem of drawing the lines defined by dual unit vectors is also resolved. Towards this direction, we propose a simple technique to calculate the surface’s striction curve in order to draw the rulings of the surface within the striction curve neighborhood. The on-screen 3D plot of the surface is realized in a pre-defined specific region close to the striction curve. With the proposed technique a natural representation of the ruled surface is derived. The shape of the surface can be intrinsically manipulated via the control lines that possess one more degree of freedom than the control points. Our method can find application not only in CAD but in the areas of NC milling and EDM