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.

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.

A Collision-Free Path Planning Method for an Articulated Mobile Robot in a Free Environment

2005 ◽  
Author(s):  
Patricia Quintero-Alvarez ◽  
Gabriel Ramirez ◽  
Sai¨d Zeghloul
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Velocity Space ◽  
Control Law ◽  
Planning Problem ◽  
Optimization Approach ◽  
Reference Velocity ◽  
Free Environment ◽  
Path Planning Problem

In our previous work, we have treated the collision-free path-planning problem for a nonholonomic mobile robot in a cluttered environment. The method we have used is based on a representation of the obstacles in the robot’s velocity space, called Feasible Velocities Polygon (FVP). Every obstacle in the robot’s influence zone is represented by a linear constraint over the robot’s velocities such that it could not be collision between the robot and the obstacle. These constraints define a convex subset in the velocity space, the FVP. Every velocity vector of the FVP ensures a safe motion for the given obstacle configuration. The path-planning problem is solved by an optimization approach between the FVP and a reference velocity to reach the goal. In this paper, we have extended our work to an articulated mobile robot. This robot is composed of a differential mobile robot as tractor and a trailer, linked by off-center joints. We have modified the reference velocity in order to consider the constraints imposed by the trailer over the robot’s velocities. The control law is a nonlinear control law, which is asymptotically stable to the goal. We use the virtual robot concept, to solve the stability problem when the robot and its trailer move backwards. An articulated mobile robot is a strongly constrained system. Even in a free environment, under some circumstances, the robot may get blocked by its trailer in its progression towards the goal. To solve these situations, we have developed a heuristic algorithm. This algorithm is based in human experience: when a blocking situation is detected, a forward-backward maneuver is made, in order to increase the distance between the tows until a maximal value. After this maneuver, the robot takes the path to the original goal. Some numerical results show that our method leads the robot and the trailer to the final position in a stable way.

scholarly journals Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics

2021 ◽  
Author(s):  
Jie Zhong ◽  
Tao Wang ◽  
Lianglun Cheng
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Free Path ◽  
Inverse Kinematics ◽  
Multiple Dimensions ◽  
Continuous State ◽  
Planning Algorithm ◽  
Convergence Performance ◽  
Path Planner ◽  
Action Spaces

AbstractIn actual welding scenarios, an effective path planner is needed to find a collision-free path in the configuration space for the welding manipulator with obstacles around. However, as a state-of-the-art method, the sampling-based planner only satisfies the probability completeness and its computational complexity is sensitive with state dimension. In this paper, we propose a path planner for welding manipulators based on deep reinforcement learning for solving path planning problems in high-dimensional continuous state and action spaces. Compared with the sampling-based method, it is more robust and is less sensitive with state dimension. In detail, to improve the learning efficiency, we introduce the inverse kinematics module to provide prior knowledge while a gain module is also designed to avoid the local optimal policy, we integrate them into the training algorithm. To evaluate our proposed planning algorithm in multiple dimensions, we conducted multiple sets of path planning experiments for welding manipulators. The results show that our method not only improves the convergence performance but also is superior in terms of optimality and robustness of planning compared with most other planning algorithms.

Path Planning for Spheres in Three Dimensional Environments With Low Interference Index

1994 ◽  
Author(s):  
Duane W. Storti ◽  
Debasish Dutta
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Configuration Space ◽  
Local Knowledge ◽  
Three Dimensional ◽  
Target Point ◽  
Planning Problem ◽  
Spherical Object ◽  
Starting Point ◽  
Path Planning Problem

Abstract We consider the path planning problem for a spherical object moving through a three-dimensional environment composed of spherical obstacles. Given a starting point and a terminal or target point, we wish to determine a collision free path from start to target for the moving sphere. We define an interference index to count the number of configuration space obstacles whose surfaces interfere simultaneously. In this paper, we present algorithms for navigating the sphere when the interference index is ≤ 2. While a global calculation is necessary to characterize the environment as a whole, only local knowledge is needed for path construction.

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.

An approach to time-optimal, smooth and collision-free path planning in a two robot arm environment

Robotica ◽  
1996 ◽  
Vol 14 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Bailin Cao ◽  
Gordon I. Dodds ◽  
George W. Irwin
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Industrial Robot ◽  
Planning Problem ◽  
Robot Arm ◽  
Rates Of Change ◽  
Time Optimal ◽  
Time Optimality ◽  
Path Planning Problem ◽  
Effective Collision

SummaryAn approach to time-optimal smooth and collision-free path planning for two industrial robot arms is presented, where path planning and joint trajectory generation are integrated. A suitable objective function, combining the requirements of time optimality and path smoothness, is proposed, which is subject to the continuity of joint trajectories, limits on their rates of change and collision-free constraints. Fast and effective collision detection for the arms is achieved using the Kuhn- Tucker conditions along with the convexity of the distance function and relying on geometrical relationships between cylinders. Nonlinear optimization is used to solve this path planning problem. The feasibility of this method is illustrated both by simulation and by experimental results.

scholarly journals A Collision-Free Path-Planning Method for an Articulated Mobile Robot

2007 ◽  
Vol 4 (2) ◽  
pp. 71-81 ◽  
Author(s):  
P. Quintero-Alvarez ◽  
G. Ramirez ◽  
S. Zeghloul
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Free Path ◽  
Planning Problem ◽  
Minimal Distance ◽  
Final Position ◽  
Cluttered Environment ◽  
Distance Calculation ◽  
Articulated Robot ◽  
Path Planning Problem

In previous works, we treated the collision-free path-planning problem for a nonholonomic mobile robot in a cluttered environment. We used a method based on a representation of the obstacles on the robot's velocity space. This representation is called Feasible Velocities Polygon (FVP). Every obstacle in the robot's influence zone is represented by a linear constraint on the robot's velocities such that a collision between the robot and the obstacle could be avoided. These constraints define a convex subset in the velocity space, the FVP. Every velocity vector in the FVP ensures a safe motion for the given obstacle configuration. The path-planning problem is solved by an optimization approach between the FVP and a reference velocity to reach the goal. In this paper, we have extended our work to an articulated mobile robot evolving in a cluttered environment. This robot is composed of a differential mobile robot and one or several modules that together form the trailer which are linked by off-center joints. This kind of robot is a strongly constrained system. Even in a free environment, under some circumstances, the robot may be blocked by its trailers in its progression towards the goal. The proposed approach, compared to other methods, has the main advantage of integrating anti-collision constraints between the articulated robot itself and the environment, in order to avoid and resolve dead-lock situations. For moving to the final position, the articulated mobile robot uses the FVP and a reference control law, to formulate the constraints method as a problem of minimal distance calculation. This formulation is then solved with the algorithm of minimal distance calculation proposed by Zeghloul (Zeghloul and Rambeaud, 1996). When a dead-locking situation arises and according to the robot–obstacle configuration, we have developed three different modules to solve these conditions. Each module uses a different approach to resolve the blocking situation. In order to show the capabilities of our method to lead the articulated robot to the final position in a stable way, a numerical result is presented.

scholarly journals Path Planning in Multi-AGVs Using a Modified A-star Algorithm

2020 ◽  
Vol 8 (5) ◽  
pp. 273-282
Author(s):  
Xing Xu ◽  
Munashe Zhoya
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Traffic Congestion ◽  
New Technologies ◽  
Grid Method ◽  
Planning Problem ◽  
Automatic Guided Vehicles ◽  
Wide Scale ◽  
Waiting Strategy ◽  
Sorting System

The problem of path planning is a hot and exclusive research topic on multiple Automatic Guided Vehicles (multi-AGVs) systems. Many research results have been reported, but outrightly solving path planning problem from the perspective of reducing traffic congestion have faced obstacles. A collision-free path planning procedure based on a modified A-star Algorithm for multi-AGVs logistics sorting system is proposed in this paper. AGVs are now a poplar way to handle materials in latest smart warehouses. Many researches have been conducted and new technologies are still being developed. There is wide scale research on algorithms to help in scheduling, routing and path planning. Multi-AGVs are used to load goods automatically in a packaging factory. To ensure an effective and safe collision free path planning, this work investigates movement, scheduling and routing, speed manipulation and efficiency of machinery to target positions. The A-star algorithm with grid method to map out a typical warehouse scenario into multiple nodes was used. To have the shortest possible path, for obstacle avoidance, we employed the Braitenberg model. The waiting strategy is used for conflict resolution at intersections.

A New Real Time Path Planning for Mobile Robot Navigation Using Invasive Weed Optimization Algorithm

2014 ◽  
Author(s):  
Prases K. Mohanty ◽  
Dayal R. Parhi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Robot Navigation ◽  
Fitness Function ◽  
Optimal Path ◽  
Mobile Robot Navigation ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Planning Algorithm ◽  
Path Planner

In this article a new optimal path planner for mobile robot navigation based on invasive weed optimization (IWO) algorithm has been addressed. This ecologically inspired algorithm is based on the colonizing property of weeds and distribution. A new fitness function has been formed between robot to goal and obstacles, which satisfied the conditions of both obstacle avoidance and target seeking behavior in robot present in the environment. Depending on the fitness function value of each weed in the colony the robot that avoids obstacles and navigating towards goal. The optimal path is generated with this developed algorithm when the robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed navigational algorithm has been performed through a series of simulation and experimental results. The results obtained from the proposed algorithm has been also compared with other intelligent algorithms (Bacteria foraging algorithm and Genetic algorithm) to show the adaptability of the developed navigational method. Finally, it has been concluded that the proposed path planning algorithm can be effectively implemented in any kind of complex environments.

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.

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