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.

Feedback motion planning of unmanned surface vehicles via random sequential composition

2019 ◽  
Vol 41 (12) ◽  
pp. 3321-3330 ◽  
Author(s):  
Emre Ege ◽  
Mustafa Mert Ankarali
Keyword(s):  
Motion Planning ◽  
Broad Class ◽  
Random Trees ◽  
Main Approach ◽  
Unmanned Surface Vehicles ◽  
Sequential Composition ◽  
Planning Algorithm ◽  
Overall Performance ◽  
Simulation Results ◽  
Feasible Solutions

In this paper, we propose a new motion planning method that aims to robustly and computationally efficiently solve path planning and navigation problems for unmanned surface vehicles (USVs). Our approach is based on synthesizing two different existing methodologies: sequential composition of dynamic behaviours and rapidly exploring random trees (RRT). The main motivation of this integrated solution is to develop a robust feedback-based and yet computationally feasible motion planning algorithm for USVs. In order to illustrate the main approach and show the feasibility of the method, we performed simulations and tested the overall performance and applicability for future experimental applications. We also tested the robustness of the method under relatively extreme environmental uncertainty. Simulation results indicate that our method can produce robust and computationally feasible solutions for a broad class of USVs.

scholarly journals Topological complexity of collision-free motion planning on surfaces

2010 ◽  
Vol 147 (2) ◽  
pp. 649-660 ◽  
Author(s):  
Daniel C. Cohen ◽  
Michael Farber
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Main Tool ◽  
Orientable Surface ◽  
Configuration Spaces ◽  
Topological Complexity ◽  
Algebraic Varieties ◽  
Hodge Structures ◽  
Lusternik Schnirelmann ◽  
Mixed Hodge Structures

AbstractThe topological complexity$\mathsf {TC}(X)$is a numerical homotopy invariant of a topological spaceXwhich is motivated by robotics and is similar in spirit to the classical Lusternik–Schnirelmann category ofX. Given a mechanical system with configuration spaceX, the invariant$\mathsf {TC}(X)$measures the complexity of motion planning algorithms which can be designed for the system. In this paper, we compute the topological complexity of the configuration space ofndistinct ordered points on an orientable surface, for both closed and punctured surfaces. Our main tool is a theorem of B. Totaro describing the cohomology of configuration spaces of algebraic varieties. For configuration spaces of punctured surfaces, this is used in conjunction with techniques from the theory of mixed Hodge structures.

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.

A real-time motion planning algorithm for a hyper-redundant set of mechanisms

Robotica ◽  
2013 ◽  
Vol 31 (8) ◽  
pp. 1327-1335 ◽  
Author(s):  
Nir Shvalb ◽  
Boaz Ben Moshe ◽  
Oded Medina
Keyword(s):  
Motion Planning ◽  
Real Time ◽  
Configuration Space ◽  
Degrees Of Freedom ◽  
Morse Function ◽  
Climbing Robot ◽  
Probabilistic Algorithm ◽  
Road Map ◽  
Time Motion ◽  
Planning Algorithm

SUMMARYWe introduce a novel probabilistic algorithm (CPRM) for real-time motion planning in the configuration space${\EuScript C}$. Our algorithm differs from a probabilistic road map (PRM) algorithm in the motion between a pair of anchoring points (local planner) which takes place on the boundary of the obstacle subspace${\EuScript O}$. We define a varying potential fieldfon ∂${\EuScript O}$as a Morse function and follow$\vec{\nabla} f$. We then exemplify our algorithm on a redundant worm climbing robot withndegrees of freedom and compare our algorithm running results with those of the PRM.

scholarly journals Development of Task-Space Nonholonomic Motion Planning Algorithm Based on Lie-Algebraic Method

2021 ◽  
Vol 11 (21) ◽  
pp. 10245
Author(s):  
Arkadiusz Mielczarek ◽  
Ignacy Dulęba
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Algebraic Method ◽  
Nonholonomic Systems ◽  
Inverse Kinematic ◽  
General Purpose ◽  
Task Space ◽  
Local Motion ◽  
Planning Algorithm ◽  
Nonholonomic Motion Planning

In this paper, a Lie-algebraic nonholonomic motion planning technique, originally designed to work in a configuration space, was extended to plan a motion within a task-space resulting from an output function considered. In both planning spaces, a generalized Campbell–Baker–Hausdorff–Dynkin formula was utilized to transform a motion planning into an inverse kinematic task known for serial manipulators. A complete, general-purpose Lie-algebraic algorithm is provided for a local motion planning of nonholonomic systems with or without output functions. Similarities and differences in motion planning within configuration and task spaces were highlighted. It appears that motion planning in a task-space can simplify a planning task and also gives an opportunity to optimize a motion of nonholonomic systems. Unfortunately, in this planning there is no way to avoid working in a configuration space. The auxiliary objective of the paper is to verify, through simulations, an impact of initial parameters on the efficiency of the planning algorithm, and to provide some hints on how to set the parameters correctly.

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.

Semi-stratified Motion Planning of Multi-agent Manipulation

2001 ◽  
Vol 5 (5) ◽  
pp. 248-256
Author(s):  
István Harmati ◽  
◽  
Ma Lantos ◽  
Shahram Payandeh ◽  
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Kinematic Model ◽  
Reference Points ◽  
Actual State ◽  
Smooth Motion ◽  
Planning Algorithm ◽  
Multi Agent ◽  
Frame Work ◽  
Selection Of

The paper addresses a manipulation problem based on kinematic model where the equations of the motion of the system can change discontinuously depending on the actual state of the system. In this case, the configuration space is stratified. The stratified control theory using the smooth motion planning algorithm promises a powerful alternative for this manipulation problem, however, it meets also some significant difficulties. The paper presents the main steps of developing computational frame work and some improvements for stratified motion planning. The concept proposes a semi-stratified method which decomposes the manipulation problem into stratified motion planning and pure finger relocation through the special selection of the reference points. Because of the different type of computational tasks (symbolic, numerical), the realization steps are also investigated.

Task-priority motion planning of underactuated systems: an endogenous configuration space approach

Robotica ◽  
2009 ◽  
Vol 28 (6) ◽  
pp. 885-892 ◽  
Author(s):  
Adam Ratajczak ◽  
Joanna Karpińska ◽  
Krzysztof Tchoń
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Robotic Systems ◽  
Planning Problem ◽  
Redundant Manipulators ◽  
Container Ship ◽  
Secondary Tasks ◽  
Planning Algorithm ◽  
Task Priority ◽  
Space Approach

SUMMARYThis paper presents a task-priority motion planning algorithm for underactuated robotic systems. The motion planning algorithm combines two features: the idea of the task-priority control of redundant manipulators and the endogenous configuration space approach. This combination results in the algorithm which solves the primary motion planning task simultaneously with one or more secondary tasks ordered in accordance with decreasing priorities. The performance of the task-priority motion planning algorithm has been illustrated with computer simulations of the motion planning problem for a container ship.

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