Instruction Generation for Assembly Operations Performed by Humans

2012 ◽  
Author(s):  
Krishnanand Kaipa ◽  
Carlos Morato ◽  
Boxuan Zhao ◽  
Satyandra K. Gupta
Keyword(s):  
Motion Planning ◽  
Free Path ◽  
Generation System ◽  
Complex Assembly ◽  
Learning Time ◽  
Design Changes ◽  
Multimodal Information ◽  
Information Text ◽  
Assembly Operations

This paper presents the design of an instruction generation system that can be used to automatically generate instructions for complex assembly operations performed by humans on factory shop floors. Multimodal information—text, graphical annotations, and 3D animations—is used to create easy-to-follow instructions. This thereby reduces learning time and eliminates the possibility of assembly errors. An automated motion planning subsystem computes a collision-free path for each part from its initial posture in a crowded scene onto its final posture in the current subassembly. Visualization of this computed motion results in generation of 3D animations. The system also consists of an automated part identification module that enables the human to identify, and pick, the correct part from a set of similar looking parts. The system’s ability to automatically translate assembly plans into instructions enables a significant reduction in the time taken to generate instructions and update them in response to design changes.

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 Survey of Robot 3D Path Planning Algorithms

2016 ◽  
Vol 2016 ◽  
pp. 1-22 ◽  
Author(s):  
Liang Yang ◽  
Juntong Qi ◽  
Dalei Song ◽  
Jizhong Xiao ◽  
Jianda Han ◽  
...  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Free Path ◽  
Optimal Path ◽  
Temporal Constraints ◽  
Three Dimension ◽  
Underwater Robots ◽  
Kinematic Constraints ◽  
Aerial Robots ◽  
Planning Algorithms

Robot 3D (three-dimension) path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints). The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path planning algorithms which have been developed in recent years and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots, and underwater robots. This paper classifies all the methods into five categories based on their exploring mechanisms and proposes a category, called multifusion based algorithms. For all these algorithms, they are analyzed from a time efficiency and implementable area perspective. Furthermore a comprehensive applicable analysis for each kind of method is presented after considering their merits and weaknesses.

scholarly journals Design of Hybrid Cells to Facilitate Safe and Efficient Human–Robot Collaboration During Assembly Operations

2018 ◽  
Vol 18 (3) ◽  
Author(s):  
Krishnanand N. Kaipa ◽  
Carlos W. Morato ◽  
Satyandra K. Gupta
Keyword(s):  
Three Dimensional ◽  
System State ◽  
Hybrid Cells ◽  
Generation System ◽  
State Monitoring ◽  
Plan Generation ◽  
3D Printed ◽  
Assembly Operations ◽  
Human Robot Collaboration

This paper presents a framework to build hybrid cells that support safe and efficient human–robot collaboration during assembly operations. Our approach allows asynchronous collaborations between human and robot. The human retrieves parts from a bin and places them in the robot's workspace, while the robot picks up the placed parts and assembles them into the product. We present the design details of the overall framework comprising three modules—plan generation, system state monitoring, and contingency handling. We describe system state monitoring and present a characterization of the part tracking algorithm. We report results from human–robot collaboration experiments using a KUKA robot and a three-dimensional (3D)-printed mockup of a simplified jet-engine assembly to illustrate our approach.

Hardness of Motion Planning with Obstacle Uncertainty in Two Dimensions

2021 ◽  
pp. 027836492199278
Author(s):  
Luke Shimanuki ◽  
Brian Axelrod
Keyword(s):  
Motion Planning ◽  
Free Path ◽  
Configuration Space ◽  
Exact Algorithm ◽  
Two Dimensions ◽  
Planning Under Uncertainty ◽  
Constant Number ◽  
3D Motion ◽  
Practical Algorithms ◽  
Case Planning

We consider the problem of motion planning in the presence of uncertain obstacles, modeled as polytopes with Gaussian-distributed faces (PGDFs). A number of practical algorithms exist for motion planning in the presence of known obstacles by constructing a graph in configuration space, then efficiently searching the graph to find a collision-free path. We show that such an exact algorithm is unlikely to be practical in the domain with uncertain obstacles. In particular, we show that safe 2D motion planning among PGDF obstacles is [Formula: see text]-hard with respect to the number of obstacles, and remains [Formula: see text]-hard after being restricted to a graph. Our reduction is based on a path encoding of MAXQHORNSAT and uses the risk of collision with an obstacle to encode variable assignments and literal satisfactions. This implies that, unlike in the known case, planning under uncertainty is hard, even when given a graph containing the solution. We further show by reduction from [Formula: see text]-SAT that both safe 3D motion planning among PGDF obstacles and the related minimum constraint removal problem remain [Formula: see text]-hard even when restricted to cases where each obstacle overlaps with at most a constant number of other obstacles.

scholarly journals Advanced algorithms for mobile robot motion planning and tracking in structured static environments using particle swarm optimization

2012 ◽  
Vol 9 (1) ◽  
pp. 9-28 ◽  
Author(s):  
Aleksandar Cosic ◽  
Marko Susic ◽  
Dusko Katic
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Planning ◽  
Free Path ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Complex Problem ◽  
Pi Controller ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Swarm Optimization

An approach to intelligent robot motion planning and tracking in known and static environments is presented in this paper. This complex problem is divided into several simpler problems. The first is generation of a collision free path from starting to destination point, which is solved using a particle swarm optimization (PSO) algorithm. The second is interpolation of the obtained collision-free path, which is solved using a radial basis function neural network (RBFNN), and trajectory generation, based on the interpolated path. The last is a trajectory tracking problem, which is solved using a proportional-integral (PI) controller. Due to uncertainties, obstacle avoidance is still not ensured, so an additional fuzzy controller is introduced, which corrects the control action of the PI controller. The proposed solution can be used even in dynamic environments, where obstacles change their position in time. Simulation studies were realized to validate and illustrate this approach.

scholarly journals Motion Planning by Integration of Multiple Policies for Complex Assembly Tasks

10.5772/10322 ◽  
2010 ◽  
Author(s):  
Natsuki Yamanobe ◽  
Hiromitsu Fujii ◽  
Tamio Arai ◽  
Ryuichi Ue
Keyword(s):  
Motion Planning ◽  
Complex Assembly ◽  
Assembly Tasks

scholarly journals A Fast Algorithm for Planning Collision-Free Paths With Rotations

1998 ◽  
Vol 120 (1) ◽  
pp. 52-57 ◽  
Author(s):  
S.-F. Chen ◽  
J. H. Oliver ◽  
D. Fernandez-Baca
Keyword(s):  
Motion Planning ◽  
Free Path ◽  
Configuration Space ◽  
Fast Algorithm ◽  
Experimental Results ◽  
Optimal Motion ◽  
Running Time ◽  
Practical Algorithm

Motion planning is a major problem in robotics. The objective is to plan a collision-free path for a robot moving through a workspace populated with obstacles. In this paper, we present a fast and practical algorithm for moving a convex polygonal robot among a set of polygonal obstacles with translations and rotations. The running time is O(c((n + k)N + n log n)), where c is a parameter controlling the precision of the results, n is the total number of obstacle vertices, k is the number of intersections of configuration space obstacles, and N is the number of obstacles, decomposed into convex objects. This work builds upon the slabbing method proposed by Ahrikencheikh et al. [2], which finds an optimal motion for a point among a set of nonoverlapping obstacles. Here, we extend the slabbing method to the motion planning of a convex polygonal robot with translations and rotations, which also allows overlapping configuration space obstacles. This algorithm has been fully implemented and the experimental results show that it is more robust and faster than other approaches.

scholarly journals A Fast Algorithm for Planning Collision-Free Paths With Rotations

1997 ◽  
Author(s):  
Shiang-Fong Chen ◽  
James H. Oliver ◽  
David Fernandez-Baca
Keyword(s):  
Motion Planning ◽  
Free Path ◽  
Configuration Space ◽  
Fast Algorithm ◽  
Experimental Results ◽  
Optimal Motion ◽  
Running Time ◽  
Practical Algorithm

Abstract Motion planning is a major problem in robotics. The objective is to plan a collision-free path for a robot moving through a workspace populated with obstacles. In this paper, we present a fast and practical algorithm for moving a convex polygonal robot among a set of polygonal obstacles with translations and rotations. The running time is O(c((n + k)N + nlogn)), where c is a parameter controlling the precision of the results, n is the total number of obstacle vertices, k is the number of intersections of configuration space obstacles, and N is the number of obstacles, decomposed into convex objects. This work builds upon the slabbing method proposed by Ahrikencheikh et al. (1994), which finds an optimal motion for a point among a set of non-overlapping obstacles. Here, we extend the slabbing method to the motion planning of a convex polygonal robot with translations and rotations, which also allows overlapping configuration space obstacles. This algorithm has been fully implemented and the experimental results show that it is more robust and faster than other approaches.

scholarly journals Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)

2021 ◽  
Vol 17 (4) ◽  
pp. 491-505
Author(s):  
G. Kulathunga ◽  
◽  
D. Devitt ◽  
R. Fedorenko ◽  
A. Klimchik ◽  
...  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Free Path ◽  
Optimal Path ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Algorithm ◽  
Feasible Path ◽  
Straight Lines ◽  
Path Planning Algorithm

Any obstacle-free path planning algorithm, in general, gives a sequence of waypoints that connect start and goal positions by a sequence of straight lines, which does not ensure the smoothness and the dynamic feasibility to maneuver the MAV. Kinodynamic-based motion planning is one of the ways to impose dynamic feasibility in planning. However, kinodynamic motion planning is not an optimal solution due to high computational demands for real-time applications. Thus, we explore path planning followed by kinodynamic smoothing while ensuring the dynamic feasibility of MAV. The main difference in the proposed technique is not to use kinodynamic planning when finding a feasible path, but rather to apply kinodynamic smoothing along the obtained feasible path. We have chosen a geometric-based path planning algorithm “RRT*” as the path finding algorithm. In the proposed technique, we modified the original RRT* introducing an adaptive search space and a steering function that helps to increase the consistency of the planner. Moreover, we propose a multiple RRT* that generates a set of desired paths. The optimal path from the generated paths is selected based on a cost function. Afterwards, we apply kinodynamic smoothing that will result in a dynamically feasible as well as obstacle-free path. Thereafter, a b-spline-based trajectory is generated to maneuver the vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. According to the experiment results, we were able to speed up the path planning task by 1.3 times when using the proposed multiple RRT* over the original RRT*.

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