Development of a trajectory planning algorithm for a 4-DoF rockbreaker based on hydraulic flow rate limits

2020 ◽  
Vol 44 (4) ◽  
pp. 501-510
Author(s):  
Louis-Francis Y. Tremblay ◽  
Marc Arsenault ◽  
Meysar Zeinali

In this paper, a novel trajectory planning methodology is proposed for use within a semi-automated hydraulic rockbreaker system. The objective of the proposed method is to minimize the trajectory duration while hydraulic fluid flow rate limits are respected. Within the trajectory planning methodology, a point-to-point path planning approach based on the decoupling of the motion of the rockbreaker’s first joint is compared with an alternative approach based on Cartesian straight-line motion. Each of these path types is parameterized as a function of time based on an imposed trajectory profile that ensures smooth rockbreaker motions. A constrained nonlinear optimization problem is formulated and solved with the trajectory duration as the objective function while constraints are applied to ensure that flow rate limits through the rockbreaker’s proportional valves and hydraulic pump are not exceeded. The proposed methodology is successfully implemented to compute a set of representative trajectories, with the path planning approach based on the decoupling of the motion of the rockbreaker’s first joint consistently producing shorter trajectory durations.

2020 ◽  
Vol 896 ◽  
pp. 224-228
Author(s):  
Mihai Dupac

In this paper a newly 3D path planning approach and curve generation for design and manufacturing efficiency is considered. The 3D path is generated by a combination of piecewise interpolating curves - along a given number of via-points - created via a spherical coordinate system specified by the polar angles, radial distances and the associated azimuthal angles. Each piecewise interpolating curve is constructed using Hermite polar interpolation in the projective polar plane and the rotating azimuthal plane. To verify the proposed approach, numerical simulations for the generation of a helix design, a 4 and 6 leaf design and a trajectory planning of a picking robot arm are conducted.


2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092004
Author(s):  
Yong-Lin Kuo ◽  
Chun-Chen Lin ◽  
Zheng-Ting Lin

This article presents a dual-optimization trajectory planning algorithm, which consists of the optimal path planning and the optimal motion profile planning for robot manipulators, where the path planning is based on parametric curves. In path planning, a virtual-knot interpolation is proposed for the paths required to pass through all control points, so the common curves, such as Bézier curves and B-splines, can be incorporated into it. Besides, an optimal B-spline is proposed to generate a smoother and shorter path, and this scheme is especially suitable for closed paths. In motion profile planning, a generalized formulation of time-optimal velocity profiles is proposed, which can be implemented to any types of motion profiles with equality and inequality constraints. Also, a multisegment cubic velocity profile is proposed by solving a multiobjective optimization problem. Furthermore, a case study of a dispensing robot is investigated through the proposed dual-optimization algorithm applied to numerical simulations and experimental work.


2013 ◽  
Vol 765-767 ◽  
pp. 413-416
Author(s):  
Jian Hong Gong ◽  
Bo Li ◽  
Xiao Guang Gao

To deal with the problem of penetration trajectory planning for UAV security issues, an improved bidirectional quintuple tree node expansion algorithm is proposed. Compare to traditional quintuple tree node expansion algorithm, the proposed algorithm could reduce the number of the expanded tree node, and it makes the bidirectional quintuple tree node expansion algorithm more efficient in path planning. By combining the bidirectional quintuple tree node expansion algorithm with multi-step optimization search mechanism, a kind of real-time UAV path planning algorithm is presented.


Author(s):  
Şahin Yıldırım ◽  
Sertaç Savaş

This chapter proposes a new trajectory planning approach by improving A* algorithm, which is a widely-used, path-planning algorithm. This algorithm is a heuristic method used in maps such as the occupancy grid map. As the resolution increases in these maps, obstacles can be defined more precisely. However, the cell/grid size must be larger than the size of the mobile robot to prevent the robot from crashing into the borders of the working environment or obstacles. The second constraint of the algorithm is that it does not provide continuous headings. In this study, an avoidance area is calculated on the map for the mobile robot to avoid collisions. Then curve-fitting methods, general polynomial and b-spline, are applied to the path calculated by traditional A* algorithm to obtain smooth rotations and continuous headings by staying faithful to the original path calculated. Performance of the proposed trajectory planning method is compared to others for different target points on the grid map by using a software developed in Labview Environment.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi Liu ◽  
Meng Joo Er ◽  
Chen Guo

Purpose The purpose of this paper is to propose an efficient path and trajectory planning method to solve online robotic multipoint assembly. Design/methodology/approach A path planning algorithm called policy memorized adaptive dynamic programming (PM-ADP) combines with a trajectory planning algorithm called adaptive elite genetic algorithm (AEGA) for online time-optimal path and trajectory planning. Findings Experimental results and comparative study show that the PM-ADP is more efficient and accurate than traditional algorithms in a smaller assembly task. Under the shortest assembly path, AEGA is used to plan the time-optimal trajectories of the robot and be more efficient than GA. Practical implications The proposed method builds a new online and efficient path planning arithmetic to cope with the uncertain and dynamic nature of the multipoint assembly path in the Cartesian space. Moreover, the optimized trajectories of the joints can make the movement of the robot continuously and efficiently. Originality/value The proposed method is a combination of time-optimal path planning with trajectory planning. The traveling salesman problem model of assembly path is established to transfer the assembly process into a Markov decision process (MDP). A new dynamic programming (DP) algorithm, termed PM-ADP, which combines the memorized policy and adaptivity, is developed to optimize the shortest assembly path. GA is improved, termed AEGA, which is used for online time-optimal trajectory planning in joints space.


AI Magazine ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 85-107 ◽  
Author(s):  
Alex Nash ◽  
Sven Koenig

In robotics and video games, one often discretizes continuous terrain into a grid with blocked and unblocked grid cells and then uses path-planning algorithms to find a shortest path on the resulting grid graph. This path, however, is typically not a shortest path in the continuous terrain. In this overview article, we discuss a path-planning methodology for quickly finding paths in continuous terrain that are typically shorter than shortest grid paths. Any-angle path-planning algorithms are variants of the heuristic path-planning algorithm A* that find short paths by propagating information along grid edges (like A*, to be fast) without constraining the resulting paths to grid edges (unlike A*, to find short paths).


Robotica ◽  
2002 ◽  
Vol 20 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Wilson D. Esquivel ◽  
Luciano E. Chiang

This paper addresses the problem of finding a nonholonomic path subject to a curvature restriction, to be tracked by a wheeled autonomous navigation vehicle. This robot is able to navigate in a structured environment, with obstacles modeled as polygons, thus constituting a model based system. The path planning methodology begins with the conditioning of the polygonal environment by offsetting each polygon in order to avoid the possibility of collision with the mobile. Next, the modified polygonal environment is used to compute a preliminary shortest path (PA) between the two extreme positions of the trajectory in the plane (x, y). This preliminary path (PA) does not yet consider the restrictions on the curvature and is formed only by straight line segments. A smoothing process follows in order to obtain a path (PS) that satisfies curvature restrictions which consist basically of joining the straight line segments by circular arcs of minimum radius R (filleting). Finally, the initial and final orientation of the vehicle are accounted for. This is done using a technique we have called the Star Algorithm, because of the geometric shape of the resulting maneuvers. A final complete path (PC) is thus obtained.


2013 ◽  
Vol 373-375 ◽  
pp. 2088-2091
Author(s):  
Quan Liang ◽  
Dong Hai Su ◽  
Jie Wang ◽  
Ye Mu Wang

For the problem of poor processing efficiency of iso-parameter tool path planning algorithm, this paper proposed a non iso-parameter trajectory planning algorithm. First established a mathematical model of five-axis machining toroid cutter, then analyzed the toroid cutter and machining surface partial differential geometric properties, proposed one kind of iso-scallop path search algorithm. Finally, using the above algorithm developed an application of trajectory planning for free-form surface and generated tool paths for such surface. The trajectories generated verified the algorithm is practicable.


Author(s):  
Abderraouf Maoudj ◽  
Abdelfetah Hentout ◽  
Brahim Bouzouia ◽  
Redouane Toumi

Manipulator robots are widely used in many fields to replace humans in complex and risky environments. However, in some particular environments the robot is prone to failure, resulting in decreased performance. In such environments, it is extremely difficult to repair the robot which interrupts the execution process. Therefore, fault tolerance plays an important role in industrial manipulators applications. In this paper, the key problems related to fault-tolerance and path planning of manipulator robots under joints failures are handled within an on-line fault-tolerant fuzzy-logic based path planning approach for high degree-of-freedom robots. This approach provides an alternative to using mathematical models to control such robots, and improves tolerance to certain faults and mechanical failures. The controller consists of two fuzzy units (i) the first unit, Fuzzy_Path_Planner, is responsible of path planning; (ii) the second unit, Fuzzy_Obstacle_Avoidance, is conceived for obstacles avoidance. Moreover, the proposed approach is capable of repelling the manipulator away from both local minima and limit cycle problems. Finally, to validate the proposed approach and show its performances and effectiveness, different tests are carried out on two six degree-of-freedom manipulator robots (ULM and PUMA560 robots), accomplishing point-to-point tasks, with and without considering some joints failures.


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