Parallel collision detection between moving robots for practical motion planning

2001 ◽  
Vol 18 (8) ◽  
pp. 487-506 ◽  
Author(s):  
Miguel Pérez-Francisco ◽  
Angel P. Del Pobil ◽  
Begoña Martínez-Salvador
Keyword(s):  
Motion Planning ◽  
Collision Detection

Real-time motion planning for robot manipulators in unknown environments using infrared sensors

Robotica ◽  
2007 ◽  
Vol 25 (2) ◽  
pp. 201-211 ◽  
Author(s):  
Shuguo Wang ◽  
Jin Bao ◽  
Yili Fu
Keyword(s):  
Motion Planning ◽  
Real Time ◽  
Collision Detection ◽  
Detection Method ◽  
Computation Time ◽  
Robot Arm ◽  
Infrared Sensors ◽  
Geometry Model ◽  
Time Motion ◽  
Series Of Experiments

SUMMARYThis paper deals with sensor-based motion planning method for a robot arm manipulator operating among unknown obstacles of arbitrary shape. It can be applied to online collision avoidance with no prior knowledge of the obstacles. Infrared sensors are used to build a description of the robot's surroundings. This approach is based on the configuration space but the construction of the C-obstacle surface is avoided. The point automation is confined on some planes with square grids in the C-space. A path-searching algorithm based on square grids is used to guide the automation maneuvering around the C-obstacles on the selected planes. To avoid the construction of the C-obstacle surface, the robot geometry model is expanded, and the static collision detection method is used. Hence, the computation time is reduced and the algorithm can work in real time. The effectiveness of the proposed method is verified by a series of experiments.

A modeling method for collision detection and motion planning of robots

Robotica ◽  
1993 ◽  
Vol 11 (3) ◽  
pp. 217-226 ◽  
Author(s):  
Chia-Ju Wu
Keyword(s):  
Linear Programming ◽  
Motion Planning ◽  
Directed Graph ◽  
Collision Detection ◽  
Convex Polyhedron ◽  
Modeling Method ◽  
Planning Problem ◽  
Linear Programming Problems ◽  
Sampling Instant ◽  
Motion Planning Problem

SUMMARYA modeling method for robots is proposed, in which a convex polyhedron is represented as a set of inequalities and a robot is represented as a union of convex polyhedrons. With this method, collision between robots can be detected by solving a set of linear programming problems at every sampling instant. By detecting possible collision at every sampling instant, a directed graph for robots is created. The motion planning problem of robots is then transformed into a path searching problem in the directed graph and can be solved by exisiting searching algorithms.

Task constrained motion planning for 7-degree of freedom manipulators with parameterized submanifolds

2018 ◽  
Vol 45 (3) ◽  
pp. 363-370 ◽  
Author(s):  
Qiang Qiu ◽  
Qixin Cao
Keyword(s):  
Motion Planning ◽  
Explicit Expression ◽  
Collision Detection ◽  
Tool Path ◽  
Degree Of Freedom ◽  
Geometric Constraints ◽  
Constrained Motion ◽  
Content Type ◽  
Planning Methods ◽  
Two Parameters

PurposeThis paper aims to use the redundancy of a 7-DOF (degree of freedom) serial manipulator to solve motion planning problems along a given 6D Cartesian tool path, in the presence of geometric constraints, namely, obstacles and joint limits.Design/methodology/approachThis paper describes an explicit expression of the task submanifolds for a 7-DOF redundant robot, and the submanifolds can be parameterized by two parameters with this explicit expression. Therefore, the global search method can find the feasible path on this parameterized graph.FindingsThe proposed planning algorithm is resolution complete and resolution optimal for 7-DOF manipulators, and the planned path can satisfy task constraint as well as avoiding singularity and collision. The experiments on Motoman SDA robot are reported to show the effectiveness.Research limitations/implicationsThis algorithm is still time-consuming, and it can be improved by applying parallel collision detection method or lazy collision detection, adopting new constraints and implementing more effective graph search algorithms.Originality/valueCompared with other task constrained planning methods, the proposed algorithm archives better performance. This method finds the explicit expression of the two-dimensional task sub-manifolds, so it’s resolution complete and resolution optimal.

Effective motion planning of manipulator based on SDPS-RRTConnect

Robotica ◽  
2021 ◽  
pp. 1-13
Author(s):  
Junxiang Xu ◽  
Jiwu Wang
Keyword(s):  
Motion Planning ◽  
Collision Detection ◽  
Local Minimum ◽  
Search Space ◽  
Fast Convergence ◽  
Good Effect ◽  
Complex Environments ◽  
Planning Time ◽  
Expansion Strategy ◽  
Strong Robustness

Abstract In order to improve the speed of motion planning, this paper proposes an improved RRTConnect algorithm (SDPS-RRTConnect) based on sparse dead point saved strategy. Combining sparse expansion strategy and dead point saved strategy, the algorithm can reduce the number of collision detection, fast convergence, avoid falling into local minimum, and ensure the completeness of search space. The algorithm is simulated in different environments. The results show that in complex environments, the sparse dead point saved strategy plays a good effect. In simple environments, the greedy connection strategy works well. Compared with the standard RRT algorithm, the standard RRTConnect algorithm, and the SDPS-RRT algorithm, the SDPS-RRTConnect algorithm has the shortest planning time, and it is suitable for both simple and complex environments. The 500 experiments show that the algorithm has strong robustness. The actual robot experiments show that the path planned by SDPS-RRTConnect algorithm is effective.

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