Robotic manipulators deployed in automation industry require high speed with precision and accuracy to perform sophisticated control tasks. Whereas, the factors like highly coupled dynamics, internal and external perturbation forces, joint friction and parameter variations degrade the performance of the manipulator. Consequently, the need of an advanced control technique or more preferably combination of multiple techniques with the capability of handling disturbances has been increased significantly. In the present research, design of Disturbance Observer (DO) based control techniques for a 6-Degree Of Freedom (DOF) robotic arm is presented to eliminate the effect of uncertainties and disturbances and to enhance the robustness of both Sliding Mode Control (SMC) and Passivity Based Control (PBC). Results demonstrate that the proposed controllers precisely estimate the torque yielded by external perturbation forces and improve the trajectory tracking performance of the system, which results in comparatively high performance of robotic manipulator in terms of speed and precision.
Robotic manipulators have reshaped industrial processes. The scientific community has witnessed an ever increasing trend in robots deployed to accomplish various tasks in industry. The complex nature and constrained requirements of robots may demand non-trivial control approaches. This paper deals with the design, simulation and hardware realization of two sophisticated control strategies: computed torque control (CTC) and variable structure control (VSC) on a pseudo-industrial manipulator with six degrees of freedom (DOF). Based on the derived kinematic and dynamic models of the robot, control laws have been formulated, which are then subjected to various test inputs in a simulation to characterize the tracking performance. The simulation results were then validated by implementing control laws on a custom-developed pseudo-industrial autonomous articulated robotic educational platform (AUTAREP). The experimental results show the effectiveness of the control strategies to track a desired trajectory. Highlights• This paper presents advanced strategies to control a highly non-linear system like a multiple Degree Of Freedom (DOF) robotic arm. • The strategies include computed torque control (CTC) and variable structure control (VSC). • Design parameters using both strategies have been investigated in a simulation. • The strategies were carried out on a custom-developed autonomous articulated robotic educational platform (AUTAREP). • Trajectory tracking results showed that the derived laws can effectively track the desired reference input for both strategies.
Subject reviewPressing requirements of improved and enhanced productivity in industrial applications has necessitated deployment of robot to automate tasks. Manipulator based articulated robots for today's industrial applications vary widely in terms of number of Degree Of Freedom (DOF), payload capacity, Range Of Motion (ROM), control implementation and mountable configurations. This paper presents a comprehensive and systematic review of industrial robots with a focus on their application areas. The study of manipulators for diversified applications has highlighted the need of sophisticated algorithms for their control and trajectory planning. Both of these key concepts are discussed in the paper. The control of industrial manipulator is important for accomplishing tasks requiring high precision, repeatability and reliability by mitigating the effects of disturbances. The trajectory planning is vital for time optimization, energy optimization and collision avoidance to ensure most appropriate trajectory for a given task in an environment. The application oriented review offers readers opportunities to generate ideas applicable to their operations and to conform feasibility of their ideas. Keywords: industrial automation; robot control; robotic manipulators; trajectory planning Automatzacija industrijskih poslova kroz mehatroničke sustave -pregled robotike iz industrijske perspektivePregledni članak Sve veći zahtjevi za poboljšanom i povećanom produktivnošću u industriji doveli su do potrebe razvoja robota u automatizaciji poslova. Zglobno vezani roboti bazirani na manipulatoru za sadašnje industrijske aplikacije uvelike variraju u odnosu na broj stupnja slobode -Degree Of Freedom (DOF), kapacitet nosivosti, raspon pokreta -Range Of Motion (ROM), provođenje kontrole i ugradnju konfiguracija. U radu se daje opsežan i sustavan pregled industrijskih robota s naglaskom na njihova područja primjene. Analiza manipulatora za različite primjene istaknula je potrebu za složenim algoritmima za njihovo upravljanje i planiranje putanje. O ovim se ključnim pitanjima raspravlja u radu. Kontrola industrijskog manipulatora je važna za obavljanje zadataka za koje je potrebna velika preciznost, ponavljanje i pouzdanost uz izbjegavanje smetnji. Planiranje putanje je od bitne važnosti za optimizaciju vremena, optimizaciju energije i izbjegavanje sudara kako bi se osigurala najprihvatljivija putanja za određeni zadatak u nekom okruženju. Pregled literature usmjeren na primjenu pruža čitateljima mogućnost da razviju ideje koje se mogu primijeniti na njihove poslove i razmisle o izvedivosti svojih ideja.
Recent advancements in the domain of robotics have offered support to humans in their everyday activities with the aim of offloading workers from performing repetitive tasks. The present work highlights one such task in garment industry where the robot may find potential to manipulate different garments including developing a number of robotic skills like laundry pile sorting, garment stacking and garment folding/ unfolding. This paper is aimed to study the integration of hardware and software developed for ClopeMa Project on a human-friendly robotic platform, i.e. a Baxter robot that can safely operate side by side with humans. In particular, the paper discusses integration of RGB-D sensor with the ROS environment and studies utility of garment manipulation. The goal is to present a working platform which can autonomously recognize the configuration of a piece of garment spread out on a flat surface. The algorithm for recognizing the garment consists of first applying Gaussian mixture model (MoG) for background subtraction and then using polygonal approximation to acquire feature points for the foreground of the garment. The proposed algorithm is tested online through series of experiments on towel, pants and t-shirts of various colors and materials. Results under varying lightening conditions witness robustness of the proposed scheme.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.