PATH PLANNING IN EXPANSIVE CONFIGURATION SPACES

1999 ◽  
Vol 09 (04n05) ◽  
pp. 495-512 ◽  
Author(s):  
DAVID HSU ◽  
JEAN-CLAUDE LATOMBE ◽  
RAJEEV MOTWANI
Keyword(s):  
Path Planning ◽  
Configuration Space ◽  
Automotive Industry ◽  
Configuration Spaces ◽  
Complex Assembly ◽  
Planning Algorithm ◽  
Robot Configuration ◽  
The Cost

We introduce the notion of expansiveness to characterize a family of robot configuration spaces whose connectivity can be effectively captured by a roadmap of randomly-sampled milestones. The analysis of expansive configuration spaces has inspired us to develop a new randomized planning algorithm. This new algorithm tries to sample only the portion of the configuration space that is relevant to the current query, avoiding the cost of precomputing a roadmap for the entire configuration space. Thus, it is well-suited for problems where only a single query is submitted for a given environment. The algorithm has been implemented and successfully applied to complex assembly maintainability problems from the automotive industry.

Collision-Free Motion Planning for an Aligned Multiple-turret System Operating in Extreme Environment

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Ümit Yerlikaya ◽  
R.Tuna Balkan
Keyword(s):  
Path Planning ◽  
Extreme Environment ◽  
Configuration Spaces ◽  
Planning Problem ◽  
Different Types ◽  
Planning Algorithm ◽  
Line Path ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
System Operating

Abstract Instead of using the tedious process of manual positioning, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular-, circular-, and torus-shaped by providing three converging options named as fast, medium, and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using six sequences and their options. The results obtained were simulated and no collision was observed between any bodies in these three options.

A novel potential-based path planning of 3-D articulated robots with moving bases

Robotica ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 359-367 ◽  
Author(s):  
Chien-Chou Lin ◽  
Chi-Chun Pan ◽  
Jen-Hui Chuang
Keyword(s):  
Path Planning ◽  
Planning Strategy ◽  
Computation Efficiency ◽  
Planning Algorithm ◽  
Minimum Potential ◽  
Potential Gradients ◽  
Robot Configuration ◽  
Articulated Robots ◽  
Repulsive Forces ◽  
Path Planning Algorithm

This paper proposes a novel path planning algorithm of 3-D articulated robots with moving bases based on a generalized potential field model. The approach computes, similar to that done in electrostatics, repulsive forces and torques between charged objects. A collision-free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these forces and torques. The proposed approach is efficient since these potential gradients are analytically tractable. In order to speedup the computation, a sequential planning strategy is adopted. Simulation results show that the proposed algorithm works well, in terms of collision avoidance and computation efficiency.

Path Planning for Origami Carton Folding With a Multi-Fingered Robotic System

2007 ◽  
Author(s):  
Wei Yao ◽  
Jian S. Dai
Keyword(s):  
Path Planning ◽  
Configuration Space ◽  
Robotic System ◽  
Test Rig ◽  
Packaging System ◽  
Mechanism Model ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Equivalent Mechanism ◽  
Robotic Fingers

This paper investigates the algorithm of origami carton folding with a multi-fingered robotic carton-packaging system. The equivalent mechanism structure of origami cartons is developed by modeling carton boards as links and creases as revolution joints. The trajectories of carton folding are analyzed by the mechanism model. Particularly the vertex of the carton is identified as a spherical linkage. A path planning algorithm is then generated based on the trajectory that is passed on to the tip of a five-bar robotic finger and the finger configuration space is identified. A test rig with two robotic fingers was developed to demonstrate the principle.

An Efficient Path-Planning Algorithm for a Robotic Manipulator by Automatic Selection Search of Indispensable Regions in Its Configuration Space

1992 ◽  
Vol 4 (5) ◽  
pp. 378-385
Author(s):  
Hiroshi Noborio ◽  
◽  
Motohiko Watanabe ◽  
Takeshi Fujii
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Configuration Space ◽  
Robotic Manipulator ◽  
Joint Space ◽  
Practical Applications ◽  
Continuous Sequence ◽  
Angle Difference ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In this paper, we propose a feasible motion planning algorithm for a robotic manipulator and its obstacles. The algorithm quickly selects a feasible sequence of collision-free motions while adaptively expanding a graph in the implicit configuration joint-space. In the configuration graph, each arc represents an angle difference of the manipulator joint; therefore, an arc sequence represents a continuous sequence of robot motions. Thus, the algorithm can execute a continuous sequence of collision-free motions. Furthermore, the algorithm expands the configuration graph only in space which is to be cluttered in the implicit configuration joint-space and which is needed to select a collision-free sequence between the initial and target positions/orientations. The algorithm maintains the configuration graph in a small size and quickly selects a collision-free sequence from the configuration graph, whose shape is to be simple enough to move the manipulator in practical applications.

Non-Nominal Path Planning of Assembly Processes

2005 ◽  
Author(s):  
Johan S. Carlson ◽  
Rikard So¨derberg ◽  
Robert Bohlin ◽  
Lars Lindkvist ◽  
Tomas Hermansson
Keyword(s):  
Path Planning ◽  
Automotive Industry ◽  
Planning Process ◽  
State Of The Art ◽  
Cost Effective ◽  
Worst Case ◽  
Positioning Systems ◽  
Planning Algorithm ◽  
On Line ◽  
Path Planning Algorithm

One important aspect in the assembly process design is to assure that there exist a collision-free assembly path for each part and subassembly. In order to reduce the need of physical verification the automotive industry use digital mock-up tool with collision checking for this kind of geometrical assembly analysis. To manually verify assembly feasibility in a digital mock-up tool can be hard and time consuming. Therefore, the recent development of efficient and effective automatic path planning algorithm and tools are highly motivated. However, in real production, all equipment, parts and subassemblies are inflicted by geometrical variation, often resulting in conflicts and on-line adjustments of off-line generated assembly paths. To avoid problems with on-line adjustments, state-of-the-art tools for path-planning can handle tolerances by a general clearance for all geometry. This is a worst-case strategy, not taking account for how part and assembly variation propagates through the positioning systems of the assembly resulting in geometry areas of both high and low degree of variation. Since, this latter approach results in unnecessary design changes or in too tight tolerances we have developed a new algorithm and working procedure enabling and supporting a more cost effective non-nominal path planning process for assembly operations. The basic idea of the paper is to combine state of the art technology within variation simulation and automatic path planning. By integrating variation and tolerance simulation results into the path planning algorithm we can allow the assembly path going closer to areas of low variation, while avoiding areas of high variation. The benefits of the proposed approach are illustrated on an industrial case from the automotive industry.

scholarly journals Exploring implicit spaces for constrained sampling-based planning

2019 ◽  
Vol 38 (10-11) ◽  
pp. 1151-1178 ◽  
Author(s):  
Zachary Kingston ◽  
Mark Moll ◽  
Lydia E Kavraki
Keyword(s):  
Motion Planning ◽  
Open Source ◽  
Configuration Space ◽  
Broad Class ◽  
Asymptotic Optimality ◽  
Configuration Spaces ◽  
Local Planning ◽  
Planning Algorithm

We present a review and reformulation of manifold constrained sampling-based motion planning within a unifying framework, IMACS (implicit manifold configuration space). IMACS enables a broad class of motion planners to plan in the presence of manifold constraints, decoupling the choice of motion planning algorithm and method for constraint adherence into orthogonal choices. We show that implicit configuration spaces defined by constraints can be presented to sampling-based planners by addressing two key fundamental primitives, sampling and local planning, and that IMACS preserves theoretical properties of probabilistic completeness and asymptotic optimality through these primitives. Within IMACS, we implement projection- and continuation-based methods for constraint adherence, and demonstrate the framework on a range of planners with both methods in simulated and realistic scenarios. Our results show that the choice of method for constraint adherence depends on many factors and that novel combinations of planners and methods of constraint adherence can be more effective than previous approaches. Our implementation of IMACS is open source within the Open Motion Planning Library and is easily extended for novel planners and constraint spaces.

scholarly journals Confidence random tree-based algorithm for mobile robot path planning considering the path length and safety

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141983817 ◽  
Author(s):  
Yong Nyeon Kim ◽  
Dong Wook Ko ◽  
Il Hong Suh
Keyword(s):  
Path Planning ◽  
Computation Time ◽  
Path Selection ◽  
Random Tree ◽  
Service Robots ◽  
Mobile Service ◽  
Rejection Method ◽  
Planning Algorithm ◽  
The Cost ◽  
Path Planning Algorithm

This article introduces a novel confidence random tree-based sampling path planning algorithm for mobile service robots operating in real environments. The algorithm is time efficient, can accommodate narrow corridors, enumerates possible solutions, and minimizes the cost of the path. These benefits are realized by incorporating notable approaches from other existing path planning algorithms into the proposed algorithm. During path selection, the algorithm considers the length and safety of each path via a sampling and rejection method. The algorithm operates as follows. First, the confidence of a path is computed based on the clearance required to ensure the safety of the robot, where the clearance is defined as the distance between the path and the closest obstacle. Then, the sampling method generates a tree graph in which the edge lengths are controlled by the confidence. In a low confidence space, such as a narrow corridor, the corresponding graph has denser samples with short edges while in a high confidence space, the samples are widely spaced with longer edges. Finally, a rejection method is employed to ensure a reasonably short computation time by optimizing the sample density by rejecting unnecessary samples. The performance of the proposed algorithm is validated by comparing the experimental results to those of several commonly used algorithms.

Path Planning for Automated Robot Painting

2007 ◽  
Author(s):  
Finlay N. McPherson ◽  
Jonathan R. Corney ◽  
Raymond C. W. Sung
Keyword(s):  
Path Planning ◽  
Light Beam ◽  
Configuration Space ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Kinematic Chain ◽  
Physical Contact ◽  
Kinematic Chains ◽  
Planning Algorithm ◽  
Rapid Prototyping And Manufacturing

This paper describes the analysis work underlying the path-planning algorithm for a robotic painting system. The system requires no bespoke production tooling and fills an automation gap in rapid prototyping and manufacturing technology that is currently occupied by hand painting. The system creates images by exposing individual pixels of a photographic coating with a robot-mounted laser. The painting process requires no physical contact so potentially images could be developed on any shape regardless of its complexity: As objects can only be “painted” when their surface can be “hit” (i.e. exposed) by the light beam the system requires six degrees of freedom to ensure all overhanging or reentrant areas can be exposed. The accuracy of serial robots degrades with the length of the kinematic chain (in other words six axis robots cannot position themselves with the same accuracy as four axis ones). Consequently to ensure high precision in the location and orientation of the light source, the object being exposed is mounted on a rotary tilt table within the workspace of a four-axis robot. This gives a six-degree of freedom positioning system composed of two separate kinematic chains. Although the resulting system is accurate the problems of constructing a coordinated path that allows the light beam to efficiently sweep (i.e. cover) the surface regardless of its geometry are challenging. This paper describes the difficulties and, after reviewing existing path planning algorithms, a new algorithm is introduced firstly by describing the nature of the system’s configuration space and then further developing this concept as an alternative to a previously described planning algorithm. Having outlined the approach the paper presents a kinematic model for the system and compares the configuration space approach to a purely Cartesian planning approach.

scholarly journals Design of basketball robot based on behavior-based fuzzy control

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142090996 ◽  
Author(s):  
Yonghong Zhi ◽  
Yan Jiang
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Autonomous Navigation ◽  
Strong Dependence ◽  
Fuzzy Rule ◽  
Planning Problem ◽  
Unknown Environment ◽  
Planning Algorithm ◽  
Behavior Based ◽  
Robot Configuration

Aiming at the strong dependence on environmental information in traditional algorithms, the path planning of basketball robots in an unknown environment, and improving the safety of autonomous navigation, this article proposes a path planning algorithm based on behavior-based module control. In this article, fuzzy control theory is applied to the behavior control structure, and these two path planning algorithms are combined to solve the path planning problem of basketball robots in an unknown environment. First, the data of each sensor of the basketball robot configuration are simply fused. Then, the obstacle distance parameters in the three directions of front, left, and right are simplified and fuzzified. Then combined with the target direction parameters, the speed, and steering of the basketball robot are controlled by fuzzy rule reasoning to realize path planning. The simulation results show that the basketball robot can overcome the uncertainty in the environment, effectively achieve good path planning, verify the feasibility of the fuzzy control algorithm, and demonstrate the validity and correctness of the path planning strategy.

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