A novel strategy for balancing the workload of industrial lines based on a genetic algorithm

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksOne major problem in industrial automation is the workload balancing problem. It consists of making the robots or, more generally, the machines, involved in the assembly process to work exactly the same, either by picking and placing the same number of pieces or by having the same number of operational cycles. This paper presents a novel strategy for solving such a problem by means of an evolutionary algorithm. The specific application of this strategy is to balance the workload of a pick-and-place process developed in the facilities of the industrial company Fameccanica Spa Data within the framework of an industrial project between the company and our research group. The novelties concerning the state-of-the-art contributions are: (1) instead of using an explicit fitness function, the candidate solutions at each iteration are evaluated by using a simulation of the entire process; (2) the parameters optimized are the velocity and acceleration of the robots involved in the line and (3) the strategy includes an algorithm for distributing the workload between the robots during the process.Peer ReviewedPostprint (author's final draft

Stroke rehabilitation using exoskeleton-based robotic exercisers: Mini review

Stroke is a debilitating disease that has afflicted millions of people throughout the world. Assisting physiotherapists in post-stroke activities to conduct rehabilitation therapies, scientific community has presented a new type of man-machine intelligent systems i.e. exoskeleton based exercisers. These devices help the patients having neurological disabilities to partially or fully regain their motor performance by applying forces to the affected finger phalanx and preventing unsuitable motion patterns. The exoskeletons because of their wide range of sensory capabilities have replaced traditional assessment of stroke patients. This article reviews developments in robotic prosthetics and exoskeletons. The primary design requirements of these devices are identified. Highlighting the authors’ research achievements in this domain, a collection of exoskeleton-based hand rehabilitation devices has been then presented with a brief description about their mechanical designs. Finally, an overall view of research in this domain is commented

Vector Maps: A Lightweight and Accurate Map Format for Multi-robot Systems

International audienceSLAM algorithms produce accurate maps that allow local-ization with typically centimetric precision. However, such a map is materialized as a large Occupancy Grid. Beside the high memory footprint, Occupancy Grid Maps lead to high CPU consumption for path planning. The situation is even worse in the context of multi-robot exploration. Indeed , to achieve coordination, robots have to share their local maps and merge ones provided by their teammates. These drawbacks of Occupancy Grid Maps can be mitigated by the use of topological maps. However, topological maps do not allow accurate obstacle delimitations needed for autonomous robots exploration. So, robots still have to handle with Occupancy Grid Maps. We argue that Vector-based Maps which materialize obstacles using collections of vectors is a more interesting alternative. Vector Maps both provide accurate metric information likewise Occupancy Grid Maps, and represent data as a graph that can be processed for path planning and maps merging as efficiently as with topological maps. Conclusions are backed by several metrics computed with several terrains that differ in size, form factor, and obstacle density

Meta-Heuristic Optimization of Sliding Mode Control—Application to Quadrotor-Based Inspection of Solar Panels

In this paper, inspection of solar energy system is addressed using a quadrotor unmanned aerial vehicle (UAV) system. The accurate positioning of the system on the solar panel requires a robust controller to precisely address the fault while ensuring stability. For this purpose, an optimized nonsingular terminal sliding mode controller (ONTSMC) is proposed. The control law is designed based on the derived quadrotor model. Particle swarm optimization (PSO) method is used to optimize the controller parameters. Also, the closed-loop stability of the controller is ensured using Lyapunov candidate function. The proposed optimized controller is simulated in MATLAB/Simulink to characterize the control performance. Results demonstrate the effectiveness of the proposed control approach

Time scheduling and optimization of industrial robotized tasks based on genetic algorithms

Today's industrial manipulators are more and more demanding in terms of productivity. This goal could be achieved by increasing speed of the robot manipulator and/or by optimizing the trajectories followed by manipulators while performing manufacturing, assembling, welding or similar tasks. Focusing on the second aspect, this research proposes a method based on genetic algorithms by exploiting CAD (computer aided design) capabilities to optimize and simulate cycle time in performing classical manufacturing tasks. The goal is to determine the shortest distance traveled by the robot manipulator in the coordinate space for every pair of successive points. In addition, our optimization procedure considers supplementary factors such as inverse kinematic model (IKM) and relative position/orientation of the manipulator w.r.t task points. All these factors were statistically assessed to determine both individual and cross influences in finding the optimal solution. The proposed approach has been validated on a real life setup, involving a 6-DOFs (degrees of freedom) industrial robot manipulator when performing a spot welding task on a car body. The obtained results are promising and show the effectiveness of the proposed strategy

Safety in Coordinated Control of Multiple Unmanned Aerial Vehicle Manipulator Systems: Case of Obstacle Avoidance

This paper treats the safety issues in coordinated transportation of an object via multiple Unmanned Aerial Vehicles with Manipulator Systems (UAVMS); in particular, the case of obstacle avoidance is considered. The proposed paradigm is based on the so-called Null-Space-based Behavioral (NSB) control approach, that allows to achieve multiple tasks simultaneously. Two different scenarios of bar transportation using multi-UAVMSs have been developed, tested and compared in simulation: in the first scenario, the obstacle avoidance is achieved at the coordination level, where the controller allows the whole system (UAVMSs and bar) to circumnavigate the obstacle; while in the second scenario only the UAVMS closest to the obstacle modifies its trajectory to overcome the obstacle by keeping the desired trajectory of the bar unchanged

Nonlinear control systems - A brief overview of historical and recent advances

Last five decades witnessed remarkable developments in linear control systems and thus problems in this subject has been largely resolved. The scope of the present paper is beyond linear solutions. Modern technology demands sophisticated control laws to meet stringent design specifications thus highlighting the increasingly conspicuous position of nonlinear control systems, which is the topic of this paper. Historical role of analytical concepts in analysis and design of nonlinear control systems is briefly outlined. Recent advancements in these systems from applications perspective are examined with critical comments on associated challenges. It is anticipated that wider dissemination of this comprehensive review will stimulate more collaborations among the research community and contribute to further developments