scholarly journals The Real-Time Path of Translation Factor IF3 onto and off the Ribosome

2007 ◽  
Vol 25 (2) ◽  
pp. 285-296 ◽  
Author(s):  
Attilio Fabbretti ◽  
Cynthia L. Pon ◽  
Scott P. Hennelly ◽  
Walter E. Hill ◽  
J. Stephen Lodmell ◽  
...  
1992 ◽  
Vol 213 (1) ◽  
pp. 204-229 ◽  
Author(s):  
P.-G. Reinhard ◽  
E. Suraud ◽  
S. Ayik

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Hongzhe Jin ◽  
Hui Zhang ◽  
Zhangxing Liu ◽  
Decai Yang ◽  
Dongyang Bie ◽  
...  

This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM) are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.


2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Jianjun Ni ◽  
Liuying Wu ◽  
Pengfei Shi ◽  
Simon X. Yang

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.


2018 ◽  
Vol 12 (1) ◽  
pp. 125-136
Author(s):  
Ravi Kumar Mandava ◽  
Mrudul Katla ◽  
Pandu R. Vundavilli

2020 ◽  
Vol 8 (12) ◽  
pp. 991
Author(s):  
Chong Wang ◽  
Kang Wang ◽  
Jiabin Tao ◽  
Yongqing Zhou

Special vehicles called transporters are used to deliver heavy blocks in the shipyard. With the development and application of information and communication technology in shipyards, the real-time positioning and ship blocks online scheduling system for transporters are being developed. The real-time path planning of transporters is important for maintaining the overall production schedule of ship blocks. Because of the large volume and heavy weight of ship blocks, there may be some problems, such as high energy consumption, block deformation and other security issues, when transporters loading a block make a turn. So, fewer turns of the transporters are also important to make a block transportation schedule. The minimum driving distance and fewer turns are considered simultaneously for transporter real-time path planning in this paper. A hybrid model considering the number of turns and the optimal path of the transporter is constructed. Moreover, the optimal scheduling model, considering path missing, is also discussed. Several shortest path algorithms are analyzed, which show that the Dijkstra algorithm is the best way to solve this model. From the attained simulation results, we demonstrate that the proposed model and algorithm have the ability to effectively solve real-time path planning for the ship block transportation in shipyards.


2014 ◽  
Author(s):  
Irving Biederman ◽  
Ori Amir
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document