Non-Nominal Path Planning of Assembly Processes

Author(s):  
Johan S. Carlson ◽  
Rikard So¨derberg ◽  
Robert Bohlin ◽  
Lars Lindkvist ◽  
Tomas Hermansson

One important aspect in the assembly process design is to assure that there exist a collision-free assembly path for each part and subassembly. In order to reduce the need of physical verification the automotive industry use digital mock-up tool with collision checking for this kind of geometrical assembly analysis. To manually verify assembly feasibility in a digital mock-up tool can be hard and time consuming. Therefore, the recent development of efficient and effective automatic path planning algorithm and tools are highly motivated. However, in real production, all equipment, parts and subassemblies are inflicted by geometrical variation, often resulting in conflicts and on-line adjustments of off-line generated assembly paths. To avoid problems with on-line adjustments, state-of-the-art tools for path-planning can handle tolerances by a general clearance for all geometry. This is a worst-case strategy, not taking account for how part and assembly variation propagates through the positioning systems of the assembly resulting in geometry areas of both high and low degree of variation. Since, this latter approach results in unnecessary design changes or in too tight tolerances we have developed a new algorithm and working procedure enabling and supporting a more cost effective non-nominal path planning process for assembly operations. The basic idea of the paper is to combine state of the art technology within variation simulation and automatic path planning. By integrating variation and tolerance simulation results into the path planning algorithm we can allow the assembly path going closer to areas of low variation, while avoiding areas of high variation. The benefits of the proposed approach are illustrated on an industrial case from the automotive industry.

Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Andreas C. Nearchou ◽  
Nikos A. Aspragathos

In some daily tasks, such as pick and place, the robot is requested to reach with its hand tip a desired target location while it is operating in its environment. Such tasks become more complex in environments cluttered with obstacles, since the constraint for collision-free movement must be also taken into account. This paper presents a new technique based on genetic algorithms (GAs) to solve the path planning problem of articulated redundant robot manipulators. The efficiency of the proposed GA is demonstrated through multiple experiments carried out on several robots with redundant degrees-of-freedom. Finally, the computational complexity of the proposed solution is estimated, in the worst case.


Author(s):  
Xu Han ◽  
Xianku Zhang

Theta* algorithm is a searching-based path planning algorithm that gives an optimal path with more flexibility on route angle than A* method. The dynamics of USV is characterized by large inertia, so that larger turning angle is preferred. In view of the shortcomings of traditional Theta* algorithm, such as being hard to balance overall situation and details in long-distance planning, and lacking of waypoint replacement scheme when a waypoint is unreachable, it is inappropriate to make long-distance planning through Theta* algorithm directly. In order to ensure safe navigation for unmanned surface vehicle (USV), this paper proposes a multi-scale Theta* algorithm to solve these defects. Simulation result manifests the proposed scheme can provide a path clear of obstacles with several fold reduction in time consumption. The proposed planning method simplifies path planning process and contributes to the development of marine transportation.


2012 ◽  
Vol 155-156 ◽  
pp. 1074-1079
Author(s):  
Zi Hui Zhang ◽  
Yue Shan Xiong

To study the path planning problem of multiple mobile robots in dynamic environments, an on-line centralized path planning algorithm is proposed. It is difficult to obtain real-time performance for path planning of multiple robots in dynamic environment. The harmonic potential field for multiple mobile robots is built by using the panel method known in fluid mechanics, which represents the outward normal velocity of each line of a polygonal obstacle as a function of the length of its characteristic line. The simulation results indicate that it is a simple, efficient and effective path planning algorithm for multiple mobile robots in the dynamic environments that the geometries and trajectories of obstacles are known in advance, and can achieve real-time performance.


2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Wing Kwong Chung ◽  
Yangsheng Xu

The energy of a space station is a precious resource, and the minimization of energy consumption of a space manipulator is crucial to maintain its normal functionalities. This paper first presents novel gaits for space manipulators by equipping a new gripping mechanism. With the use of wheels locomotion, lower energy demand gaits can be achieved. With the use of the proposed gaits, we further develop a global path planning algorithm for space manipulators which can plan a moving path on a space station with a minimum total energy demand. Different from existing approaches, we emphasize both the use of the proposed low energy demand gaits and the gaits composition during the path planning process. To evaluate the performance of the proposed gaits and path planning algorithm, numerous simulations are performed. Results show that the energy demand of both the proposed gaits and the resultant moving path is also minimum.


Robotica ◽  
1993 ◽  
Vol 11 (3) ◽  
pp. 245-251 ◽  
Author(s):  
Cyrille Froissart ◽  
Pierre Mechler†

SUMMARYA method is presented to perform path planning in the Cartesian space. The motion velocity and acceleration are continuous. This is the first polynomial path planning algorithm in the Cartesian space working in real-time; it does not need an advanced knowledge of the trajectory and can be used when knot points are provided on-line by a sensor. The Bézier representation is used to compute a fifth degree polynomial path. It has been tested on an industrial robot controller.


2010 ◽  
Vol 20-23 ◽  
pp. 1192-1198
Author(s):  
Xian Yi Cheng ◽  
Qian Zhu ◽  
Zhen Wen Zhang

To improve the poor efficiency in path planning that caused by not taking RoboCup’s stamina, character, dynamic starting point, dynamic endpoint and other factors into consideration in the path planning process, the RoboCup path planning is generalized as a multi-objective optimization problem in the paper, and proposes RoboCup’s sport model with dynamic multi-objective path planning which is based on RoboCup’s stamina triple model, and a path planning algorithm that is suited for RoboCup is advanced based on PFNPGA ( Penalty Function Niche Pareto Genetic Algorithm). The experiment in a real environment shows that, by comparing with traditional path planning methods, the algorithm in the paper can get more reasonable path at the premise of guarantee RoboCup have relative high stamina values.


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