scholarly journals Minimum Energy Demand Locomotion on Space Station

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Wing Kwong Chung ◽  
Yangsheng Xu
Keyword(s):  
Path Planning ◽  
Energy Demand ◽  
Planning Process ◽  
Minimum Energy ◽  
Space Station ◽  
Space Manipulators ◽  
Planning Algorithm ◽  
Precious Resource ◽  
Path Planning Algorithm ◽  
Moving Path

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.

Non-Nominal Path Planning of Assembly Processes

2005 ◽  
Author(s):  
Johan S. Carlson ◽  
Rikard So¨derberg ◽  
Robert Bohlin ◽  
Lars Lindkvist ◽  
Tomas Hermansson
Keyword(s):  
Path Planning ◽  
Automotive Industry ◽  
Planning Process ◽  
State Of The Art ◽  
Cost Effective ◽  
Worst Case ◽  
Positioning Systems ◽  
Planning Algorithm ◽  
On Line ◽  
Path Planning Algorithm

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.

Multi-scale theta* algorithm for the path planning of unmanned surface vehicle

2021 ◽  
pp. 147509022110396
Author(s):  
Xu Han ◽  
Xianku Zhang
Keyword(s):  
Path Planning ◽  
Planning Process ◽  
Optimal Path ◽  
Long Distance ◽  
Unmanned Surface Vehicle ◽  
Safe Navigation ◽  
Multi Scale ◽  
Fold Reduction ◽  
Planning Algorithm ◽  
Path Planning Algorithm

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.

scholarly journals Energy optimization path planning for battery-powered agricultural rover

2018 ◽  
Vol 173 ◽  
pp. 02001
Author(s):  
Cong Niu ◽  
Xiutian Yan
Keyword(s):  
Path Planning ◽  
Energy Optimization ◽  
Battery Life ◽  
Simulation Studies ◽  
Straight Line ◽  
Planning Algorithm ◽  
Save Energy ◽  
Line Path ◽  
Path Planning Algorithm ◽  
Moving Path

Battery life is critical for battery-powered agricultural rovers, so techniques such as optimized moving path planning are of great significance in this field. Finding an optimized path other than straight-line path could save energy and prolong the battery life. Compared with traditional straight-line path planning, an energy-optimized path planning is realized based on artificial potential field algorithm. In simulation studies, most of the uphill is avoided and at least 10.15 % of energy is saved with the optimized path planning. We believe this energy optimization path planning algorithm is a feasible solution to extend the battery life for field operated agricultural rover.

scholarly journals Design and Ground Verification of Space Station Manipulator Control Method for Orbital Replacement Unit Changeout

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Bingshan Hu ◽  
Feng Chen ◽  
Liangliang Han ◽  
Huanlong Chen ◽  
Hongliu Yu
Keyword(s):  
Path Planning ◽  
Control Method ◽  
Impedance Control ◽  
Space Station ◽  
Open Loop ◽  
Control Algorithms ◽  
Experiment Platform ◽  
Planning Algorithm ◽  
Application Requirements ◽  
Path Planning Algorithm

Chinese space station has been in construction phase, and it will be launched around 2020. Lots of orbital replacement units (ORUs) are installed on the space station, and they need to be replaced on orbit by a manipulator. In view of above application requirements, the control method for ORU changeout is designed and verified in this paper. Based on the analysis of the ORU changeout task flow, requirements of space station manipulator’s control algorithms are presented. The open loop path planning algorithm, close loop path planning algorithm based on visual feedback, and impedance control algorithm are researched. To verify the ORU changeout task flow and corresponding control algorithms, a ground experiment platform is designed, which includes a 6-DOF manipulator with a camera and a force/torque sensor, an end effector with clamp/release and screwing function, ORU module, and ORU store. At last, the task flow and control algorithms are verified on the test platform. Through the research, it is found that the ORU changeout task flow designed in this paper is reasonable and feasible, and the control method can be used to control a manipulator to complete the ORU changeout task.

The Research on Path Planning Algorithm of RoboCup Based on PFNPGA

2010 ◽  
Vol 20-23 ◽  
pp. 1192-1198
Author(s):  
Xian Yi Cheng ◽  
Qian Zhu ◽  
Zhen Wen Zhang
Keyword(s):  
Path Planning ◽  
Optimization Problem ◽  
Planning Process ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The Poor ◽  
Starting Point ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

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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