scholarly journals A Hybrid Path-Planning Strategy for Mobile Robots with Limited Sensor Capabilities

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1049 ◽  
Author(s):  
Guilherme de Oliveira ◽  
Kevin de Carvalho ◽  
Alexandre Brandão
Keyword(s):  
Path Planning ◽  
Avoidance Task ◽  
Planning Problem ◽  
Local Planning ◽  
Mapping Algorithm ◽  
Planning Strategy ◽  
Algorithm Efficiency ◽  
Cost Efficient ◽  
Environment Experiment ◽  
Path Planner

This paper introduces a strategy for the path planning problem for platforms with limited sensor and processing capabilities. The proposed algorithm does not require any prior information but assumes that a mapping algorithm is used. If enough information is available, a global path planner finds sub-optimal collision-free paths within the known map. For the real time obstacle avoidance task, a simple and cost-efficient local planner is used, making the algorithm a hybrid global and local planning solution. The strategy was tested in a real, cluttered environment experiment using the Pioneer P3-DX and the Xbox 360 kinect sensor, to validate and evaluate the algorithm efficiency.

scholarly journals Research and Implementation of Robot Path Planning Based onVSLAM

2018 ◽  
Vol 160 ◽  
pp. 06004
Author(s):  
Zi-Qiang Wang ◽  
He-Gen Xu ◽  
You-Wen Wan
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Planning Problem ◽  
A Algorithm ◽  
Algorithm Efficiency ◽  
Grid Map ◽  
Localization And Mapping ◽  
Improve Algorithm ◽  
Path Planning Problem ◽  
Robot Path

In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM) to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM) for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.

A local-based method for manipulators path planning, using sub-goals resulting from a local graph

Robotica ◽  
2006 ◽  
Vol 24 (5) ◽  
pp. 539-548 ◽  
Author(s):  
S. Zeghloul ◽  
C. Helguera ◽  
G. Ramirez
Keyword(s):  
Path Planning ◽  
Local Environment ◽  
Linear Constraints ◽  
Geometric Constraints ◽  
Planning Problem ◽  
Cluttered Environments ◽  
Free Position ◽  
Local Methods ◽  
Path Planner ◽  
Path Planning Problem

This paper addresses the path planning problem for manipulators. The problem of path planning in robotics can be defined as follows: To find a collision free trajectory from an initial configuration to a goal configuration. In this paper a collision-free path planner for manipulators, based on a local constraints method, is proposed. In this approach the task is described by a minimization problem under geometric constraints. The anti-collision constraints are mapped as linear constraints in the configuration space and they are not included in the function to minimize. Also, the task to achieve is defined as a combination of two displacements. The first displacement brings the robot towards to the goal configuration, while the second one allows the robot to avoid the local minima. This formulation solves many of classical problems found in local methods. However, when the robot acts in some heavy cluttered environments, a zig-zaging phenomenon could appear. To solve this situation, a graph based on the local environment of the robot is constructed. On this graph, an A* search is performed, in order to find a dead-lock free position that can be used as a sub-goal in the optimization process. This path-planner has been implemented within SMAR, a CAD-Robotics system developed at our laboratory. Tests in heavy cluttered environments were successfully performed.

Online cooperative path planning for multi-quadrotors in an unknown dynamic environment

2021 ◽  
pp. 095441002110166
Author(s):  
Zhenyue Jia ◽  
Ping Lin ◽  
Jiaolong Liu ◽  
Luyang Liang
Keyword(s):  
Path Planning ◽  
Partial Information ◽  
Three Dimensional ◽  
Dynamic Environment ◽  
Planning Problem ◽  
Planning Strategy ◽  
Coordination Strategy ◽  
Planning Strategies ◽  
Feasible Path ◽  
Path Planning Problem

The online cooperative path planning problem is discussed for multi-quadrotor maneuvering in an unknown dynamic environment. Based on the related basic concepts, typical three-dimensional obstacle models, such as spherical and cubic, and their collision checking criteria are presented in this article. An improved rapidly exploring random tree (RRT) algorithm with goal bias and greed property is proposed based on the heuristic search strategy to overcome the shortcomings of the classical RRT algorithm. Not only are the kinematic constraints of the quadrotor established but the time and space coordination strategy matching with the improved RRT algorithm is also presented in this article. Furthermore, a novel online collision avoidance strategy according to the partial information of the surrounding environment is proposed. On the basis of the above work, a distributed online path planning strategy is proposed to obtain the feasible path for each quadrotor. Numerical simulation results show that the improved RRT algorithm has better search efficiency than the classical RRT algorithm. And the satisfactory path planning and path tracking results prove that the above model and related planning strategies are reasonable and effective.

scholarly journals Two agents with GBFS algorithms working cooperatively to get a shortest path

2020 ◽  
Vol 25 (3) ◽  
pp. 448-454
Author(s):  
José Andrés Chaves Osorio ◽  
Juan Bernardo Gómez Mendoza ◽  
Edward Andrés González Rios
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Cooperative Work ◽  
Cooperative Strategy ◽  
Planning Strategy ◽  
Two Agents ◽  
Best First Search ◽  
Cooperative Team ◽  
Path Planner ◽  
Traveled Distances

This study is carried out in order to verify if the implementation of the concept of cooperative work among two agents, that use path planners A* to obtain the shortest path (previous work of the authors) is also valid when the cooperative strategy is applied using another path planner such as the so-called GBFS (Greedy Best First Search). In this sense, this paper shows a path planning strategy that combines the capabilities of two Agents each one with its own path planner GBFS (slightly different from each other) in order to obtain the shortest path. The comparisons between paths are made by analyzing the behavior and results obtained from the agents operating in different forms: (1) Working individually; (2) Working as a team (cooperating and exchanging information). The results show that in all analyzed situations are obtained shortest traveled distances when the path planners work as a cooperative team.

scholarly journals Efficient Path Planning of Secondary Additive Manufacturing Operations

2018 ◽  
Vol 249 ◽  
pp. 03011
Author(s):  
Keimargeo McQueen ◽  
Sara Darensbourg ◽  
Carl Moore ◽  
Tarik Dickens ◽  
Clement Allen
Keyword(s):  
Additive Manufacturing ◽  
Path Planning ◽  
Travelling Salesman Problem ◽  
Optimal Path ◽  
Planning Problem ◽  
Robotic Arms ◽  
Optimal Path Planning ◽  
Manufacturing Operations ◽  
3D Printed ◽  
Path Planner

We have designed a path planner for an additive manufacturing (AM) prototype that consists of two robotic arms which collaborate on a single part. Theoretically, with two nozzle equipped arms, a part can be 3D printed twice as fast. Moreover, equipping the second robot with a machining tool enables the completion of secondary operations like hole reaming or surface milling before the printing is finished. With two arms in the part space care must be taken to ensure that the arms collaborate intelligently; in particular, tasks must be planned so that the robots do not collide. This paper discusses the development of a robot path planner to efficiently print segments with two arms, while maintaining a safe distance between them. A solution to the travelling salesman problem, an optimal path planning problem, was used to successfully determine the robots path plans while a simple nozzle-to-nozzle distance calculation was added to represent avoiding robot-to-robot collisions. As a result, in simulation, the average part completion time was reduced by 45% over the single nozzle case. Importantly, the algorithm can theoretically be run on n-robots, so time reduction possibilities are large.

scholarly journals Ellipsoidal Path Planning for Unmanned Aerial Vehicles

2021 ◽  
Vol 11 (17) ◽  
pp. 7997
Author(s):  
Carlos Villaseñor ◽  
Alberto A. Gallegos ◽  
Gehova Lopez-Gonzalez ◽  
Javier Gomez-Avila ◽  
Jesus Hernandez-Barragan ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Clustering Algorithms ◽  
Computational Cost ◽  
Mapping Algorithm ◽  
Planning Strategy ◽  
Aerial Vehicles ◽  
Planning Algorithm ◽  
Trained Neural Network ◽  
Path Planning Algorithm

The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids and clustering algorithms. The EMA computes compact in-memory maps, but still with enough information to accurately represent the environment and to be useful for robot navigation algorithms. In this work, we develop a novel path planning algorithm based on a bio-inspired algorithm for navigation in the ellipsoidal map. Our approach overcomes the problem that there is no closed formula to calculate the distance between two ellipsoidal surfaces, so it was approximated using a trained neural network. The presented path planning algorithm takes advantage of ellipsoid entities to represent obstacles and compute paths for small UAVs regardless of the concavity of these obstacles, in a very geometrically explicit way. Furthermore, our method can also be used to plan routes in dynamical environments without adding any computational cost.

Development of a path follower in real-time environment

2017 ◽  
Vol 14 (4) ◽  
pp. 297-306 ◽  
Author(s):  
B.B.V.L. Deepak ◽  
M.V.A. Raju Bahubalendruni
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Optimal Path ◽  
Shortest Paths ◽  
Planning Problem ◽  
Content Type ◽  
Ground Vehicle ◽  
Planning Strategy ◽  
Institute Of Technology ◽  
The Given

Purpose The purpose of this paper is to study the path-planning problem of an unmanned ground vehicle (UGV) in a predefined, structured environment. Design/methodology/approach In this investigation, the environment chosen was the roadmap of the National Institute of Technology, Rourkela, obtained from Google maps as reference. An UGV is developed and programmed so as to move autonomously from an indicated source location to the defined destination in the given map following the most optimal path. Findings An algorithm based on linear search is implemented to the autonomous robot to generate shortest paths in the environment. The developed algorithm is verified with the simulations as well as in experimental environments. Originality/value Unlike the past methodologies, the current investigation deals with the global path-planning strategy as the line following mechanism. Moreover, the proposed technique has been implemented in a real-time environment.

A Novel Method for SUAV Path Planning Based on MPC

2012 ◽  
Vol 616-618 ◽  
pp. 2153-2157
Author(s):  
Hang Yu Wang
Keyword(s):  
Path Planning ◽  
Predictive Control ◽  
Planning Problem ◽  
Planning Strategy ◽  
Control Actions ◽  
Small Uav ◽  
Novel Method ◽  
Effective Path ◽  
Path Planning Problem ◽  
Special Strategy

Path planning has always being one of the most significant study fields in Small UAV researching. And Model Predictive Control (MPC) is a special strategy in obtaining the control actions which were achieved by solving a finite horizon optimal control problem at each instant. The paper advanced a novel method which was called Model Predictive Path Planning Strategy (MPPS) based on MPC to deal with the SUAV path planning problem and a responding predictive planner was put forward to generate an effective path for SUAV in simulative urban environment. The results of the simulation show that the advanced method can be used to plan path for SUAV.

Collision-free path planning for nonholonomic mobile robots using a new obstacle representation in the velocity space

Robotica ◽  
2001 ◽  
Vol 19 (5) ◽  
pp. 543-555 ◽  
Author(s):  
Gabriel Ramírez ◽  
Saïd Zeghloul
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Nonholonomic Constraints ◽  
Linear Constraints ◽  
Velocity Space ◽  
Mobile Robot Navigation ◽  
Planning Problem ◽  
Nonholonomic Mobile Robots ◽  
Distance Information ◽  
Path Planner

This paper presents a collision-free path planner for mobile robot navigation in an unknown environment subject to nonholonomic constraints. This planner is well adapted for use with embarked sensors, because it uses only the distance information between the robot and the obstacles. The collision-free path-planning is based on a new representation of the obstacles in the velocity space. The obstacles in the influence zone are mapped as linear constraints into the velocity space of the robot, forming a convex subset that represents the velocities that the robot can use without collision with the objects. The planner is composed by two modules, termed “reaching the goal” and “boundary following”. The major advantages of this method are the very short calculation time and a continuous stable behavior of the velocities. The results presented demonstrate the capabilities of the proposed method for solving the collision-free path-planning problem.

Path Planning for Autonomous Car Parking

2018 ◽  
Author(s):  
Letian Lin ◽  
J. Jim Zhu
Keyword(s):  
Path Planning ◽  
Target Line ◽  
Planning Problem ◽  
Control Laws ◽  
Computational Costs ◽  
Planning Algorithm ◽  
Path Planner ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
Reverse Path

The path planning problem for autonomous car parking has been widely studied. However, it is challenging to design a path planner that can cope with parking in tight environment for all common parking scenarios. The important practical concerns in design, including low computational costs and little human’s knowledge and intervention, make the problem even more difficult. In this work, a path planner is developed using a novel four-phase algorithm. By using some switching control laws to drive two virtual cars to a target line, a forward path and a reverse path are obtained. Then the two paths are connected along the target line. As illustrated by the simulation results, the proposed path planning algorithm is fast, highly autonomous, sufficiently general and can be used in tight environment.

Sign in / Sign up

Export Citation Format

Share Document