Renato Tinós

A self-organizing random immigrants genetic algorithm for dynamic optimization problems

In this paper a genetic algorithm is proposed where the worst individual and individuals with indices close to its index are replaced in every generation by randomly generated individuals for dynamic optimization problems. In the proposed genetic algorithm, the replacement of an individual can affect other individuals in a chain reaction. The new individuals are preserved in a subpopulation which is defined by the number of individuals created in the current chain reaction. If the values of fitness are similar, as is the case with small diversity, one single replacement can affect a large number of individuals in the population. This simple approach can take the system to a self-organizing behavior, which can be useful to control the diversity level of the population and hence allows the genetic algorithm to escape from local optima once the problem changes due to the dynamics.

Motion and force control of cooperative robotic manipulators with passive joints

In this paper, robotic systems when two or more underactuated manipulators are working in a cooperative way are studied. The underactuation effects on object to be controlled and on load capacity of the cooperative arms are analyzed. A hybrid control of motion and squeeze force is proposed. For the motion control, a Jacobian matrix that relates the torques in the actuated joints to the resulting force in the load is obtained. In addition, a method to compute the dynamic load-carrying capacity of cooperative manipulators with passive joints is presented. Results of the control system are verified in simulations and in an actual system formed by two cooperative arms.

A Fault Tolerance Framework for Cooperative Robotic Manipulators

In this chapter we present a fault tolerance framework for cooperative manipulators. The fault detection and isolation (FDI) system uses the kinematic constraints of the cooperative system and neural networks to detect and treat four categories of faults: free-swinging joint faults (FSJF), where one or more joints lose actuation and become free-swinging; locked joint faults (LJF), where one or more joints become locked; incorrectly-measured joint position faults (JPF), where the measurement of one or more joint positions is incorrect; and incorrectly-measured joint velocity faults (JVF), where the measurement of one or more joint velocities is incorrect. After the faults are detected by the FDI system, the control system is reconfigured according to the nature of the isolated fault and the manipulation task is resumed.

Continuous dynamic problem generators for evolutionary algorithms

Addressing dynamic optimization problems has attracted a growing interest from the evolutionary algorithm community in recent years due to its importance in the applications of evolutionary algorithms in real world problems. In order to study evolutionary algorithms in dynamic environments, one important work is to develop benchmark dynamic environments. This paper proposes two continuous dynamic problem generators. Both generators use linear transformation to move individuals, which preserves the distance among individuals. In the first generator, the linear transformation of individuals is equivalent to change the direction of some axes of the search space while in the second one it is obtained by successive rotations in different planes. Preliminary experiments were carried out to study the performance of some standard genetic algorithms in continuous dynamic environments created by the proposed generators.

Hyper-selection in dynamic environments

In recent years, several approaches have been developed for genetic algorithms to enhance their performance in dynamic environments. Among these approaches, one kind of methods is to adapt genetic operators in order for genetic algorithms to adapt to a new environment. This paper investigates the effect of the selection pressure on the performance of genetic algorithms in dynamic environments. A hyper-selection scheme is proposed for genetic algorithms, where the selection pressure is temporarily raised whenever the environment changes. The hyper-selection scheme can be combined with other approaches for genetic algorithms in dynamic environments. Experiments are carried out to investigate the effect of different selection pressures on the performance of genetic algorithms in dynamic environments and to investigate the effect of the hyper-selection scheme on the performance of genetic algorithms in combination with several other schemes in dynamic environments. The experimental results indicate that the effect of the hyper-selection scheme depends on the problem under consideration and other schemes combined in genetic algorithms.

Fault tolerant localization for teams of distributed robots

To combine sensor information from distributed robot teams, it is critical to know the locations of all the robots relative to each other. This paper presents a novel fault tolerant localization algorithm developed for centimeter-scale robots, called Millibots. To determine their locations, the Millibots measure the distances between themselves with an ultrasonic distance sensor. They then combine these distance measurements with dead reckoning in a maximum likelihood estimator. The focus of this paper is on detecting and isolating measurement faults that commonly occur in this localization system. Such failures include dead reckoning errors when the robots collide with undetected obstacles, and distance measurement errors due to destructive interference between direct and multi-path ultrasound wavefronts. Simulations show that the fault tolerance algorithm accurately detects erroneous measurements and significantly improves the reliability and accuracy of the localization system.

Fault tolerance in cooperative manipulators

The problem of fault tolerance in cooperative manipulators rigidly connected to a solid object is addressed in this paper. Four faults are considered: free-swinging joint faults, locked joint faults, incorrect measured joint position, and incorrect measured joint velocity. The faults are first detected by a, fault detection and isolation system. Free-swinging and locked joint faults are isolated using artificial neural networks. The other faults are isolated based on the kinematic constraints imposed on the cooperative system. After the isolation of the faults, the control system is reconfigured. Control laws for the system with passive or locked joints are developed. Results of the fault tolerance system applied in simulations and in a real cooperative system are presented.

Generalized asymmetric partition crossover (GAPX) for the asymmetric TSP

The Generalized Partition Crossover (GPX) constructs new solutions for the Traveling Salesman Problem (TSP) by finding recombining partitions with one entry and one exit in the graph composed by the union of two parent solutions. If there are k recombining partitions in the union graph, 2^k-2 solutions are simultaneously exploited by GPX. Generalized Asymmetric Partition Crossover (GAPX) is introduced; it finds more recombining partitions and can also find partitions for the asymmetric TSP. GAPX does this by locating partitions that cut vertices of degree 4 in the union graph and by finding partitions with multiple entry and exit points, both in O(n) time. GAPX can improve the quality of solutions generated by the Lin-Kernighan-Helsgaun heuristic and improve the state of the art for the asymmetric TSP.

An analysis of the XOR dynamic problem generator based on the dynamical system

In this paper, we use the exact model (or dynamical system approach) to describe the standard evolutionary algorithm (EA) as a discrete dynamical system for dynamic optimization problems (DOPs). Based on this dynamical system model, we analyse the properties of the XOR DOP Generator, which has been widely used by researchers to create DOPs from any binary encoded problem. DOPs generated by this generator are described as DOPs with permutation, where the fitness vector is changed according to a permutation matrix. Some properties of DOPs with permutation are analyzed, which allows explaining some behaviors observed in experimental results. The analysis of the properties of problems created by the XOR DOP Generator is important to understand the results obtained in experiments with this generator and to analyze the similarity of such problems to real world DOPs.

Control of cooperative manipulators with passive joints

The problem of the control of cooperative manipulators with passive joints and are rigidly connected to a solid object is addressed in this paper. Passive joints can appear due to free-swinging joint failures or can be an intrinsic characteristic of the robots. A hybrid control of motion and squeeze force is proposed. For this purpose, a Jacobian matrix relating velocities in the actuated joints and load velocity is obtained based on the kinematic constraints of the cooperative system. Results of the control system applied in simulations and in real robots are presented.