This paper presents the results of the experimental tests performed to validate the functionality of a variable pitch system (VPS), designed for pitch attitude control of the novel underwater robotic vehicle explorer UX-1. The VPS is composed of a mass suspended from a central rod mounted across the hull. This mass is rotated around the transverse axis of the vehicle in order to perform a change in the inclination angle for navigation in vertical mine shafts. In this work, the equations of motion are first derived with a quaternion attitude representation, and are then extended to include the dynamics of the VPS. The performance of the VPS is demonstrated in real underwater experimental tests that validate the pitch angle control independently, and coupled with the heave motion control system.

In the last years, we have been working on exploring alternative actuation technologies for the future service and personal robots. These shall allow designing lighter and safer robots, devoid of conventional mechanical transmission mechanisms i.e. motor-less and gear-less robots. Here, we summarise our work with Shape Memory Alloys. We show that, despite their known limitations, by finding suitable niches of application, dedicated mechatronics design, and ad-hoc control strategies, SMAs can effectively be used as an alternative actuation technology for robotic systems.

In this paper we present an approach for analyzing the inertial effects of changing the wing shape for steering a bat-like robot. Using BaTboT, a robotic platform with massive morphing-wings, we have estimated the generation of pitching and rolling torques, which are directly related to forward and turning maneuvers. Results let us conclude that faster retraction of the wings during the upstroke, and slower extension during the downstroke increase both pitching and rolling torques in about 50% compared to those wingbeats with equal periods for retraction/extension. Also, we determined that the pitch torque generation is proportional to 0.6m1/f, whereas the rolling torque is promotional to 0.1m1/f, being m the mass of the robot and f the flapping frequency of the wings.

This paper presents the design, implementation and validation of a novel spherical Autonomous Underwater \nVehicle (AUV) prototype, developed for inspection and exploration of flooded mine tunnel networks. The unique mechanical, electrical and hardware design is presented, as well as the development of a theoretical 6 degree-of-freedom (DOF) highfidelity dynamic model of the system. A series of underwater experiments were carried out in a controlled environment to test the standard motion patterns of the AUV with a Proportional-Integral-Derivative (PID) controller. The performance of the PID controller will be used as the baseline for comparison of more advanced control schemes. The experimental results demonstrated that the spherical AUV was able to realize the tested underwater motions with notable performance.

This paper describes the UX-1 underwater mine exploration robotic system under development in the context of the UNEXMIN project. UNEXMIN is an international innovation action funded under the EU H2020 program, aiming to develop new technologies and services allowing the exploration of flooded underground mines. The system is comprised by the UX-1 robot prototype, launch and recovery system, command and control subsystem and a data management and post-processing computational infrastructure. The UX-1 robot is a small spherical robot equipped with a multibeam sonar, five digital cameras and rotating laser line structured light systems. It is capable of obtaining an accurate point cloud of the surrounding environment along with high resolution imagery. A set of mineralogy, water parameters and geophysical sensors was also developed in order to obtain a more comprehensive mine model. These comprise a multi-spectral camera, electro-conductivity, pH, magnetic field sensors, a subbottom sonar, total natural gamma-ray detector, UV-light for fluorescent observation and a water sampling unit. The design of the system is presented along with the robot design. Some preliminary results are also presented and discussed.

In this paper, we put forward an interval type-2 fuzzy neural network (IT2FNN) to deal with control issues of nonlinear systems with uncertainties. The fuzzy rules of the IT2FNN use interval type-2 triangular fuzzy sets to account for antecedent parts and adopt crisp numbers for the corresponding consequents. To effectively cope with uncertainties in the systems, a sliding-mode-control theory-based approach with new parameter learning rules is proposed to update the IT2FNN. The overall stability of the proposed methodology is also proved by using appropriate Lyapunov functions. Finally, the proposed method is applied to control the angular position of an inverted pendulum system. Simulation results indicate that, compared to a conventional proportional-derivative controller, the IT2FNN with the proposed learning rules can eliminate the uncertainties in performance and efficiently track the angle trajectory as desired.

Bat wings contain dozens of joints that enable the animal to perform aggressive maneuvers by means of changing the wing shape during flight. There is evidence that the inertial forces produced by their wings during flapping have a key role in the attitude movements of the animal, i.e. aerial rotations. In fact, bats efficiently generate net body forces to manoeuvre by taking advantage of their large wing-to-body mass ratio. In this paper, the following question is formulated: Could a Micro Aerial Vehicle (MAV) inspired by the biomechanics of bats take advantage of the morphing-wings aimed at increasing net body forces? Using BaTboT, a novel bat-like MAV with highly articulated wings actuated by shape memory alloy actuators, our goal is to quantify the effects of different wing modulation patterns on the generation of net body forces. Experiments are carried out to confirm the important physical role that changing the wing shape enables: the contraction time of the wings (upstroke) should be faster than the extension time (downstroke), taking about 37.5% of the wingbeat period. This modulation pattern has enabled a lift force increment of 22% (from L = 0.92N to L = 1.12N), abrupt drag reduction (from D = 0.22N to D = 0.11N) and also an increase of net body forces (F net ) about 28% compared to those wing modulation patterns defined with equal periods for contraction/extension. These findings can be useful for accurate dynamics modelling and efficient design of flight controllers applied to morphing-wing micro aerial vehicles.

In this paper, we present our current work in the design and characterisation of a new shape memory alloy (SMA)-based High Phase Order Motor (HPOM). The motor can be used either in stepping mode or in servo mode of operation. Each phase of the motor consists of an SMA wire with a spring. The principle of operation of the HPOM is presented. In its operation the motor resembles a stepper motor though the actuation principles are different and hence has been characterised similar to a stepper motor.This motor can be actuated in either direction depending on which SMA is actuated, which are presented in this work. The motor is modelled and simulated and the results of simulations and experiments are presented.

The complexity in the execution of cooperative tasks is high due to the fact that a robot team requires movement coordination at the beginning of the mission and continuous coordination during the execution of the task. A variety of techniques have been proposed to give a solution to this problem assuming standard mobile robots. This work focuses on presenting the execution of a cooperative task by a modular robot team. The complexity of the task execution increases due to the fact that each robot is composed of modules which have to be coordinated in a proper way to successfully work. A combined tight and loose cooperation strategy is presented and a bar-pushing example is used as a cooperative task to show the performance of this type of system.

In this paper, we describe our current work on bio-inspired locomotion systems using a deformable structure and smart materials, concretely Shape Memory Alloys, exploring the possibility of building motor-less and gear-less robots. A swimming underwater robot has been developed whose movements are generated using such actuators, used for bending the backbone of the fish, which in turn causes a change on the curvature of the body. This paper focuses on how standard swimming patterns can be reproduced with the proposed design, using an actuation dynamics model identified in prior work.

An important topic in the field of Multi Robot Systems focuses on motion coordination and synchronization for formation keeping. Although several works have addressed such problem, little attention has been devoted to study the computational complexity within the framework of large-scale systems. This paper presents our current work on how to achieve high computational performance for systems composed by a large number of robots that must fulfill with a marching and formation task. A scalable Multi-Processor Parallel Architecture is introduced with the purpose of achieving scalability, i.e., computation time of O(log2n) for a n-robots system. Our architecture has been tested onto a multi-processor system and validated against several simulations testing.

In this paper, we present a negotiation protocol for simultaneous task subdivision and allocation for heterogeneous multi-robot systems. An abstraction of the concept of task is presented that allows to apply the protocol on a variety of tasks. The negotiation adopts Rubinstein's alternate offers protocol, where offers are evaluated and generated using a heuristic search step. The protocol has been tested on computer simulations.

In this paper, we present an application to Search and Rescue of a task negotiation protocol for teams of heterogeneous robots. Self-organization through autonomous negotiations allow the robots to assign themselves a number of target observation points decided by the operator, who is relieved from deciding the optimal assignment. The operator can then focus on monitoring the mission and deciding next actions. The protocol has been tested on both computer simulations and real robots.

The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison.

The dynamic optimization problem concerns finding an optimum in a changing environment. In the tracking problem, the optimizer should be able to follow the optimum's changes over time.In this paper we present two adaptive mutation operators designed to improve the following of a time-changing optimum, under the assumption that the changes follow a non-random law. Such law can be estimated in order to improve the optimum tracking capabilities of the algorithm. For experimental assessment, a (1,λ) evolution strategy has been applied to a dynamic version of the sphere problem.

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

Several evolutionary algorithms have been proposed for the satisfiability problem. We review the solution representations suggested in literature and choose the most promising one - the bit string representation - for further evaluation. An empirical comparison on commonly used benchmarks is presented for the most successful evolutionary algorithms and for WSAT, a prominent local search algorithm for the satisfiability problem. The key features of successful evolutionary algorithms are identified, thereby providing useful methodological guidelines for designing new heuristics. Our results indicate that evolutionary algorithms are competitive to WSAT.

The author proposes a heuristic based evolutionary algorithm for the maximum clique problem. The algorithm is based on a local search heuristic centered on a continuous formulation of the problem which is approached with a class of dynamical systems called replicator equations. We show how, embedding this local search heuristic within an evolutionary algorithm, helps the replicator equation heuristic to find larger cliques, and leads to an effective algorithm for the maximum clique problem. Experimental results performed on a class of benchmark instances from the literature assess the effectiveness of the proposed algorithm.