Control and obstacle avoidance of a WMR, based on sliding-mode, ultrasounds and laser

Ciubucciu, George; Filipescu, Adrian; Filipescu, Silviu; Dumitrascu, Bogdan

doi:10.1109/icca.2016.7505373

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…Additionally, an obstacle avoidance method based on sonars and ultrasounds was implemented [5,9,10]; • control loop for RM Cyton 1500 based on eye in hand VSS for precise positioning for picking up work-piece from ARS PeopleBot. The eye in hand VSS camera is mounted on the end effector of RM Cyton 1500; • control loop for RM Cyton 1500 based on inverse kinematic for transporting work-piece and eye to hand VSS2 to release it on P/RML.…”

Section: Real-time Control Of P/rml With Integrated Arss Rms and Vsssmentioning

confidence: 99%

“…Using the specialized image processing toolbox from MATLAB and the control input defined in equations ( 30) and (32), the synchronization between all control loops is implemented. Figure 15 describes the trajectory with obstacle avoidance of ARS PeopleBot assisting P/RML based on TT-SMC and sensitivity bubble method (sonars located on bottom platform), [10,[25][26][27]. The sensitivity bubble, shown in Figure 16, depends on the speed of movement of the robot and allows a good detection of obstacles.…”

Section: Real-time Control Of P/rml With Integrated Arss Rms and Vsssmentioning

confidence: 99%

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Manufacturing Technology on a Mechatronics Line Assisted by Autonomous Robotic Systems, Robotic Manipulators and Visual Servoing Systems

2020

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This paper proposes the implementation of an assisting technology to a processing/reprocessing mechatronics line (P/RML), comprising the following: two autonomous robotic systems (ARSs), two robotic manipulators (RMs) and three visual servoing systems (VSSs). The P/RML has four line-shaped workstations assisted by two ARSs—wheeled mobile robots (WMRs): one of them equipped with an RM, used for manipulation, and the other one used for transport. Two types of VSSs—eye to hand and eye in hand—are used as actuators for precise positioning of RMs to catch and release the work-piece. The work-piece visits stations successively as it is moved along the line for processing. If the processed piece does not pass the quality test, it is taken from the last stations of the P/RML and it is transported to the first station where it will be considered for reprocessing. The P/RML, assisted by ARSs, RMs and VSSs, was modelled with the synchronized hybrid Petri nets (SHPN). To control the ARSs, we propose the use of trajectory-tracking and sliding-mode control (TTSMC). The precise positioning that allows the picking up and releasing of the work-piece was performed using two types of VSSs. In the case of the first one, termed eye to hand VSS, the cameras have a fixed position, located at the last and the first workstations of the P/RML. For the second one, named eye in hand VSS, the camera is located at the end effector of the RM.

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Section: Real-time Control Of P/rml With Integrated Arss Rms and Vsssmentioning

confidence: 99%

Section: Real-time Control Of P/rml With Integrated Arss Rms and Vsssmentioning

confidence: 99%

Manufacturing Technology on a Mechatronics Line Assisted by Autonomous Robotic Systems, Robotic Manipulators and Visual Servoing Systems

2020

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“…In addition, several notable works have successfully solved path tracking control problem of WMR using techniques such as sliding mode control [3], adaptive control [4], and backstepping control [5]. However, it should be noted that most of the work assumed that ideally there would be no wheel slippage or skidding occurrences during vehicle movements [6].…”

Section: Introductionmentioning

confidence: 99%

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

Rustam¹,

Tahir²,

Yassin³

et al. 2022

TEM Journal

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In this paper, the operability of a custombuilt differential drive wheel mobile robot was evaluated using a self-driving algorithm in practical application. Several key parameters need to be realized by the WMR to enable succinct self-driving algorithm evaluations and parameter derivations. The main components of the WMR development were examined in this work, specifically parameter derivations, hardware implementation, steering algorithm and WMR operability. The result obtained indicate that with proper design and careful calibration of sensors, the required driving parameters could be realized. This enables the WMR to potentially serve as data collection platform for future evaluation of self-driving algorithms.

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“…The manufacturing line is characterized by the operations to be performed in the workstations using the monitoring and control systems, CAS, ARS, RM, MVS which give reparability and flexibility features for processing and reprocessing operations [4][5][6][7][8]. The structure of the P/RML highlights the system's overall functions: the automatic processing of parts, transport, handling, storing and the automatic control of all the devices integrated in the system using the PLCs in different configurations: centralized or distributed.…”

Section: Introductionmentioning

confidence: 99%

“…For this, the processing/reprocessing planning also requires complex operations to be performed such as performance measurement and evaluation, kinematics control, system planning, and resources management. For a P/RML assisted by CAS, a preparing strategy adapted to the characteristics of the system is more effective than the techniques used from domainindependent methods [6][7][8][9][10][11]. If the final workpiece does not pass the quality test, the task planner will provide the optimal sequence to reprocess the product.…”

Section: Introductionmentioning

confidence: 99%

Mobile Visual Servoing Based Control of a Complex Autonomous System Assisting a Manufacturing Technology on a Mechatronics Line

et al. 2022

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The main contribution of this paper is the modeling and control for a complex autonomous system (CAS). It is equipped with a visual sensor to operate precision positioning in a technology executed on a laboratory mechatronics line. The technology allows the retrieval of workpieces which do not completely pass the quality test. Another objective of this paper is the implementation of an assisting technology for a laboratory processing/reprocessing mechatronics line (P/RML) containing four workstations, assisted by the following components: a complex autonomous system that consists of an autonomous robotic system (ARS), a wheeled mobile robot (WMR) PeopleBot, a robotic manipulator (RM) Cyton 1500 with seven degrees of freedom (7 DOF), and a mobile visual servoing system (MVS) with a Logitech camera as visual sensor used in the process of picking, transporting and placing the workpieces. The purpose of the MVS is to increase the precision of the RM by utilizing the look and move principle, since the initial and final positions of the CAS can slightly deviate from their trajectory, thus increasing the possibility of errors to appear during the process of catching and releasing the pieces. If the processed piece did not pass the quality test and has been rendered as defective, it is retrieved from the last station of the P/RML and transported to the first station for reprocessing. The control of the WMR is done using the trajectory-tracking sliding-mode control (TTSMC). The RM control is based on inverse kinematics model, and the MVS control is implemented with the image moments method.

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Control and obstacle avoidance of a WMR, based on sliding-mode, ultrasounds and laser

Cited by 7 publications

References 13 publications

Manufacturing Technology on a Mechatronics Line Assisted by Autonomous Robotic Systems, Robotic Manipulators and Visual Servoing Systems

Manufacturing Technology on a Mechatronics Line Assisted by Autonomous Robotic Systems, Robotic Manipulators and Visual Servoing Systems

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

Mobile Visual Servoing Based Control of a Complex Autonomous System Assisting a Manufacturing Technology on a Mechatronics Line

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