Optimization-based path planning framework for industrial manufacturing processes with complex continuous paths

Weingartshofer, Thomas; Bischof, Bernhard; Meiringer, M.; Hartl-Nesic, Christian; Kugi, Andreas

doi:10.1016/j.rcim.2022.102516

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…The GA optimization capabilities were used to produce an ideal path and memory-based lookup was employed for local optimization to update the most efficient paths between different map intersections. In [105] presented a modified ant system (AS) algorithm as a genetic algorithm methodology for real-time global optimal path planning of wheeled mobile robots. The proposed approach involves using the MAKLINK graph theory to create the free space model of the robot, the Dijkstra algorithm to find a suboptimal collision-free path, and the modified AS algorithm to optimize the location of the suboptimal path to generate the globally optimal path.…”

Section: Genetic Algorithm Techniquementioning

confidence: 99%

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Borkar,

Aljrees,

Pandey

et al. 2023

Processes

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Wheeled mobile robots (WMRs) have been a focus of research for several decades, particularly concerning navigation strategies in static and dynamic environments. This review article carefully examines the extensive academic efforts spanning several decades addressing navigational complexities in the context of WMR route analysis. Several approaches have been explored by various researchers, with a notable emphasis on the inclusion of stability and intelligent capabilities in WMR controllers attracting the attention of the academic community. This study traces historical and contemporary WMR research, including the establishment of kinetic stability and the construction of intelligent WMR controllers. WMRs have gained prominence in various applications, with precise navigation and efficient control forming the basic prerequisites for their effective performance. The review presents a comprehensive overview of stability analysis and navigation techniques tailored for WMRs. Initially, the exposition covers the basic principles of WMR dynamics and kinematics, explaining the different wheel types and their associated constraints. Subsequently, various stability analysis approaches, such as Lyapunov stability analysis and passivation-based control, are discussed in depth in the context of WMRs. Starting an exploration of navigation techniques, the review highlights important aspects including path planning and obstacle avoidance, localization and mapping, and trajectory tracking. These techniques are carefully examined in both indoor and outdoor settings, revealing their benefits and limitations. Finally, the review ends with a comprehensive discussion of the current challenges and possible routes in the field of WMR. The discourse includes the fusion of advanced sensors and state-of-the-art control algorithms, the cultivation of more robust and reliable navigation strategies, and the continued exploration of novel WMR applications. This article also looks at the progress of mobile robotics during the previous three decades. Motion planning and path analysis techniques that work with single and multiple mobile robots have been discussed extensively. One common theme in this research is the use of soft computing methods to give mobile robot controllers cognitive behaviors, such as artificial neural networks (ANNs), fuzzy logic control (FLC), and genetic algorithms (GAs). Nevertheless, there is still a dearth of applications for mobile robot navigation that leverage nature-inspired algorithms, such as firefly and ant colony algorithms. Remarkably, most studies have focused on kinematics analysis, with a small number also addressing dynamics analysis.

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Section: Genetic Algorithm Techniquementioning

confidence: 99%

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Borkar,

Aljrees,

Pandey

et al. 2023

Processes

View full text Add to dashboard Cite

show abstract

“…However, due to low-power built-in cobot actuators (in comparison with standard industrial robot arms), their introduction in a machining process requires more careful trajectory planning in order to ensure the feasibility of the robot task, especially in the case of manufacturing processes with complex continuous paths where the complexity of robot path planning increases significantly [21]. Optimal relative workpiece/robot placement and robot path/trajectory planning considering this issue thus become even more important in order to provide a rapid setup of a robotic system in flexible high mix/low volume applications.…”

Section: Introductionmentioning

confidence: 99%

“…The researchers optimized the location of the robot to generate maximum task-space velocity with minimum joint velocities [23]. For robot-to-workpiece placement for large-scale welding systems [24], the authors generated a kinematic performance map based on a kinetostatic condition index that was used to optimize robot configurations in a polishing application [25], introduced a custom index for robot-based placement optimization demonstrated in a trim application in shoe manufacturing [26], and optimized a workpiece placement for the robotic operation in challenging manufacturing tasks [27,28] and surface finishing [21,29]. An interesting new optimization approach was also introduced to maximize the available velocities of the end-effector during a task execution of path following in robot machining called the decomposed twist feasibility method [30].…”

Section: Introductionmentioning

confidence: 99%

Toward Optimal Robot Machining Considering the Workpiece Surface Geometry in a Task-Oriented Approach

Hace

2024

Mathematics

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Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot’s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.

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Section: Introductionmentioning

confidence: 99%

Toward Optimal Robot Machining considering the Workpiece Surface Geometry in a Task-Oriented Approach

Hace

2023

Preprint

View full text Add to dashboard Cite

Robot workpiece machining is interesting in industry since it offers some advantages, such as higher flexibility in comparison with the conventional approach based on the CNC technology. However, in recent years we have been facing a strong progressive shift to custom based manufacturing and low volume/high mix production, which require a novel approach to automation by the employment of collaborative robotics. However, collaborative robots feature only limited motion capability, to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the characteristics of the workpiece surface constraint in the robot kinematic analysis, that enables evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot`s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.

show abstract

Optimization-based path planning framework for industrial manufacturing processes with complex continuous paths

Cited by 8 publications

References 34 publications

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Toward Optimal Robot Machining Considering the Workpiece Surface Geometry in a Task-Oriented Approach

Toward Optimal Robot Machining considering the Workpiece Surface Geometry in a Task-Oriented Approach

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