scholarly journals Tool accessibility with path and motion planning for robotic drilling and riveting

2021 ◽  
Author(s):  
David Dakdouk
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Maximum Velocity ◽  
Software Application ◽  
Robotic Drilling ◽  
Aerospace Manufacturing ◽  
Shortest Distance ◽  
Tool Accessibility ◽  
S Curve ◽  
Maximum Production Rate

Robotic applications in aerospace manufacturing and aircraft assembly today are limited. This is because most of the aircraft parts are relatively small or have complex shapes that make tasks like robotic drilling and riveting more challenging. These challenges include tool accessibility, path planning, and motion planning. In this thesis, a process methodology was developed to overcome the tool accessibility challenges facing robotic drilling and riveting for aircraft parts. The tool accessibility was analyzed based on the Global Accessibility Area and the Global Accessibility Volume to determine the accessible boundaries for parts with zero, one and two surfaces curvatures. The path planning was optimized based on the shortest distance, least number of steps, and minimal tool orientation change. The motion planning was optimized based on the s-curve using the robot’s maximum velocity and acceleration for minimum cycle time and maximum production rate. A software application was developed to simulate the tasks.

scholarly journals Tool accessibility with path and motion planning for robotic drilling and riveting

2021 ◽  
Author(s):  
David Dakdouk
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Maximum Velocity ◽  
Software Application ◽  
Robotic Drilling ◽  
Aerospace Manufacturing ◽  
Shortest Distance ◽  
Tool Accessibility ◽  
S Curve ◽  
Maximum Production Rate

Robotic applications in aerospace manufacturing and aircraft assembly today are limited. This is because most of the aircraft parts are relatively small or have complex shapes that make tasks like robotic drilling and riveting more challenging. These challenges include tool accessibility, path planning, and motion planning. In this thesis, a process methodology was developed to overcome the tool accessibility challenges facing robotic drilling and riveting for aircraft parts. The tool accessibility was analyzed based on the Global Accessibility Area and the Global Accessibility Volume to determine the accessible boundaries for parts with zero, one and two surfaces curvatures. The path planning was optimized based on the shortest distance, least number of steps, and minimal tool orientation change. The motion planning was optimized based on the s-curve using the robot’s maximum velocity and acceleration for minimum cycle time and maximum production rate. A software application was developed to simulate the tasks.

Tool Accessibility Analysis for Robotic Drilling and Fastening

2017 ◽  
Vol 139 (9) ◽  
Author(s):  
David Dakdouk ◽  
Fengfeng Xi
Keyword(s):  
Work Environment ◽  
Work Environments ◽  
Design Team ◽  
Software Application ◽  
Robotic Drilling ◽  
Aerospace Manufacturing ◽  
Complex Shapes ◽  
Tool Accessibility ◽  
Process Methodology ◽  
Robotic Applications

Robotic applications in aerospace manufacturing and aircraft assembly today are limited. This is because most of the aircraft parts are relatively crowded and have complex shapes that make tasks like robotic drilling and fastening more challenging. These challenges include tool accessibility, path, and motion planning. In this paper, a process methodology was developed to overcome the tool accessibility challenges facing robotic drilling and riveting for aircraft parts that are located in crowded work environments. First, the tool accessibility was analyzed based on the global accessibility area (GAA) and the global accessibility volume (GAV) to determine the accessible boundaries for parts with zero, one, and two surfaces curvatures. Then, the path for the tool was generated while taking in consideration the approachability planning. This approach generates a number of intermediate points that enable the tool to maneuver around obstacles to reach the final target points if they are accessible. Last, a software application was developed to simulate the drilling and riveting tasks, and to validate the proposed process. The results of the simulation confirmed the proposed methodology and provided a numerical feedback describing the level of crowdedness of the work environment. The accessibility percentage can then be used by the design team to reduce the design complexity and increase the level of tool accessibility.

Avoidance of obstacles with unknown trajectories: locally optimal paths and path complexity, Part II

Robotica ◽  
1993 ◽  
Vol 11 (5) ◽  
pp. 403-412 ◽  
Author(s):  
James Gil de Lamadrid ◽  
Jill Zimmermanf
Keyword(s):  
Path Planning ◽  
Maximum Velocity ◽  
Local Information ◽  
Planning Problem ◽  
Two Dimensional ◽  
Robot Trajectory ◽  
Optimal Paths ◽  
Sensor Information ◽  
Minimum Velocity ◽  
Path Planning Problem

SUMMARYContinuing the work presented in part I, ‡ we consider the problem of moving a point robot through a two dimensional workspace containing polygonal obstacles moving on unknown trajectories. We propose to use sensor information to predict the trajectories of the obstacles, and interleave path planning and execution. We define a locally minimum velocity path as an optimal robot trajectory, given only local information about obstacle trajectories. We show that the complexity of a path planning problem can be characterized by how frequently the robot must change directions to approximate the locally minimum velocity path. Our results apply to both robots with and without maximum velocity limits.

scholarly journals Robot Motion Planning in an Unknown Environment with Danger Space

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 201 ◽  
Author(s):  
Hadi Jahanshahi ◽  
Mohsen Jafarzadeh ◽  
Naeimeh Najafizadeh Sari ◽  
Viet-Thanh Pham ◽  
Van Van Huynh ◽  
...  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Markov Decision Processes ◽  
Free Space ◽  
Optimal Path ◽  
Humanoid Robots ◽  
Decision Processes ◽  
Inference System ◽  
Unknown Environment ◽  
Markov Decision

This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted to cross when no free space options are available. In other words, the danger can be defined as the potentially risky areas of the map. For example, mud pits in a wooded area and greasy floor in a factory can be considered as a danger. The synthetic potential field, linguistic method, and Markov decision processes are methods which have been reviewed for path planning in a free-danger unknown environment. The modified Markov decision processes based on the Takagi–Sugeno fuzzy inference system is implemented to reach the target in the presence and absence of the danger space. In the proposed method, the reward function has been calculated without the exact estimation of the distance and shape of the obstacles. Unlike other existing path planning algorithms, the proposed methods can work with noisy data. Additionally, the entire motion planning procedure is fully autonomous. This feature makes the robot able to work in a real situation. The discussed methods ensure the collision avoidance and convergence to the target in an optimal and safe path. An Aldebaran humanoid robot, NAO H25, has been selected to verify the presented methods. The proposed methods require only vision data which can be obtained by only one camera. The experimental results demonstrate the efficiency of the proposed methods.

Autonomous Rectilinear Motion Planning for a Spatial Robot: Path Planning for a Spatial 4R Manipulator With a Single Spherical Obstacle Inside the Workspace

1992 ◽  
Vol 114 (4) ◽  
pp. 559-563 ◽  
Author(s):  
Menq-Dar Shieh ◽  
J. Duffy
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Free Path ◽  
Efficient Algorithm ◽  
Rectilinear Motion ◽  
Robot Path Planning ◽  
End Effector ◽  
Truncated Pyramid ◽  
Robot Path

This is the first of a series of papers dealing with the path planning for a spatial 4R robot with multiple spherical obstacles inside the workspace. In this paper, a time efficient algorithm has been developed to determine a collision free path for the end effector tip of the robot with a single spherical obstacle inside the workspace. A truncated pyramid and a right circular torus are used to model the nonreachable workspaces of the end effector tip of the robot. The problem of guiding the spatial 4R manipulator while avoiding a spherical obstacle is reduced to moving a point while avoiding a truncated pyramid and/or a right circular torus inside the workspace. The point represents the tip of the end effector of the manipulator. This approach produces an efficient algorithm for determining a collision free path. The algorithm has been successfully developed and implemented in the Silicon Graphics 4D-70GT workstation to verify the results.

scholarly journals An approach for real-time motion planning of an inchworm robot in complex steel bridge environments

Robotica ◽  
2016 ◽  
Vol 35 (6) ◽  
pp. 1280-1309 ◽  
Author(s):  
David Pagano ◽  
Dikai Liu
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Real Time ◽  
Line Of Sight ◽  
Steel Bridge ◽  
Time Motion ◽  
3D Environments ◽  
3D Scenarios ◽  
End Node ◽  
2D And 3D

SUMMARYPath planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach.

scholarly journals Optimal Motion Planning in GPS-Denied Environments Using Nonlinear Model Predictive Horizon

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5547
Author(s):  
Younes Al Younes ◽  
Martin Barczyk
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Real Time ◽  
Nonlinear Model ◽  
Feedback Linearization ◽  
Autonomous Vehicle ◽  
Flight Test ◽  
Local Path Planning ◽  
Planning Approach ◽  
Local Path

Navigating robotic systems autonomously through unknown, dynamic and GPS-denied environments is a challenging task. One requirement of this is a path planner which provides safe trajectories in real-world conditions such as nonlinear vehicle dynamics, real-time computation requirements, complex 3D environments, and moving obstacles. This paper presents a methodological motion planning approach which integrates a novel local path planning approach with a graph-based planner to enable an autonomous vehicle (here a drone) to navigate through GPS-denied subterranean environments. The local path planning approach is based on a recently proposed method by the authors called Nonlinear Model Predictive Horizon (NMPH). The NMPH formulation employs a copy of the plant dynamics model (here a nonlinear system model of the drone) plus a feedback linearization control law to generate feasible, optimal, smooth and collision-free paths while respecting the dynamics of the vehicle, supporting dynamic obstacles and operating in real time. This design is augmented with computationally efficient algorithms for global path planning and dynamic obstacle mapping and avoidance. The overall design is tested in several simulations and a preliminary real flight test in unexplored GPS-denied environments to demonstrate its capabilities and evaluate its performance.

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