scholarly journals Navigation of Autonomous Light Vehicles Using an Optimal Trajectory Planning Algorithm

2021 ◽  
Vol 13 (3) ◽  
pp. 1233
Author(s):  
Ángel Valera ◽  
Francisco Valero ◽  
Marina Vallés ◽  
Antonio Besa ◽  
Vicente Mata ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Trajectory Planning ◽  
Autonomous Navigation ◽  
Optimal Trajectory ◽  
Computational Cost ◽  
Initial Point ◽  
Target Point ◽  
Software Components ◽  
Planning Algorithm ◽  
Optimal Trajectory Planning

Autonomous navigation is a complex problem that involves different tasks, such as location of the mobile robot in the scenario, robotic mapping, generating the trajectory, navigating from the initial point to the target point, detecting objects it may encounter in its path, etc. This paper presents a new optimal trajectory planning algorithm that allows the assessment of the energy efficiency of autonomous light vehicles. To the best of our knowledge, this is the first time in the literature that this is carried out by minimizing the travel time while considering the vehicle’s dynamic behavior, its limitations, and with the capability of avoiding obstacles and constraining energy consumption. This enables the automotive industry to design environmentally sustainable strategies towards compliance with governmental greenhouse gas (GHG) emission regulations and for climate change mitigation and adaptation policies. The reduction in energy consumption also allows companies to stay competitive in the marketplace. The vehicle navigation control is efficiently implemented through a middleware of component-based software development (CBSD) based on a Robot Operating System (ROS) package. It boosts the reuse of software components and the development of systems from other existing systems. Therefore, it allows the avoidance of complex control software architectures to integrate the different hardware and software components. The global maps are created by scanning the environment with FARO 3D and 2D SICK laser sensors. The proposed algorithm presents a low computational cost and has been implemented as a new module of distributed architecture. It has been integrated into the ROS package to achieve real time autonomous navigation of the vehicle. The methodology has been successfully validated in real indoor experiments using a light vehicle under different scenarios entailing several obstacle locations and dynamic parameters.

scholarly journals Time-jerk optimal trajectory planning of hydraulic robotic excavator

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110346
Author(s):  
Yunyue Zhang ◽  
Zhiyi Sun ◽  
Qianlai Sun ◽  
Yin Wang ◽  
Xiaosong Li ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
High Efficiency ◽  
Optimal Solution ◽  
Optimal Time ◽  
Target Point ◽  
Robotic Excavator ◽  
The Impact ◽  
Optimal Trajectory Planning

Due to the fact that intelligent algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE) are susceptible to local optima and the efficiency of solving an optimal solution is low when solving the optimal trajectory, this paper uses the Sequential Quadratic Programming (SQP) algorithm for the optimal trajectory planning of a hydraulic robotic excavator. To achieve high efficiency and stationarity during the operation of the hydraulic robotic excavator, the trade-off between the time and jerk is considered. Cubic splines were used to interpolate in joint space, and the optimal time-jerk trajectory was obtained using the SQP with joint angular velocity, angular acceleration, and jerk as constraints. The optimal angle curves of each joint were obtained, and the optimal time-jerk trajectory planning of the excavator was realized. Experimental results show that the SQP method under the same weight is more efficient in solving the optimal solution and the optimal excavating trajectory is smoother, and each joint can reach the target point with smaller angular velocity, and acceleration change, which avoids the impact of each joint during operation and conserves working time. Finally, the excavator autonomous operation becomes more stable and efficient.

Optimal Trajectory Generation for Robotic Manipulators Using Dynamic Programming

1987 ◽  
Vol 109 (2) ◽  
pp. 88-96 ◽  
Author(s):  
S. Singh ◽  
M. C. Leu
Keyword(s):  
Dynamic Programming ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robotic Manipulators ◽  
Planning Algorithm ◽  
Manipulator Link ◽  
On Line ◽  
And Performance ◽  
Two Stages ◽  
Optimal Trajectory Planning

The problem of optimal control of robotic manipulators is dealt with in two stages: (1) optimal trajectory planning, which is performed off-line and results in the prescription of the position and velocity of each link as a function of time along a “given” path and (2) on-line trajectory tracking, during which the manipulator is guided along the planned trajectory using a feedback control algorithm. In order to obtain a general trajectory planning algorithm which could account for various constraints and performance indices, the technique of dynamic programming is adopted. It is shown that for a given path, this problem is reduced to a search over the velocity of one moving manipulator link. The design of the algorithm for optimal trajectory planning and the relevant computational issues are discussed. Simulations are performed to test the effectiveness of this method. The use of this algorithm in conjunction with an on-line controller is also presented.

Time Optimal Path Planning of Palletizing Robot

2013 ◽  
Vol 470 ◽  
pp. 658-662
Author(s):  
Yong Pan Xu ◽  
Ying Hong
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Path ◽  
Straight Path ◽  
Optimal Path Planning ◽  
Quintic Polynomial ◽  
Time Optimal ◽  
Acceleration And Deceleration ◽  
Planning Algorithm ◽  
Optimal Trajectory Planning

In order to improve the efficiency and reduce the vibration of Palletizing Robot, a new optimal trajectory planning algorithm is proposed. This algorithm is applied to the trajectory planning of Palletizing manipulators. The S-shape acceleration and deceleration curve is adopted to interpolate joint position sequences. Considering constraints of joint velocities, accelerations and jerks, the traveling time of the manipulator is minimized. The joint interpolation confined by deviation is used to approximate the straight path, and the deviation is decreased significantly by adding only small number of knots. Traveling time is solved by using quintic polynomial programming strategy between the knots, and then time-jerk optimal trajectories which satisfy constraints are planned. The results show that the method can avoid the problem of manipulator singular points and improve the palletize efficiency.

scholarly journals Curve-based Approach for Optimal Trajectory Planning with Optimal Energy Consumption: application to Wheeled Mobile Robots

2020 ◽  
Vol 53 (2) ◽  
pp. 9670-9675
Author(s):  
Inderjeet Singh ◽  
Manarshhjot Singh ◽  
Ismail Bensekrane ◽  
Othman Lakhal ◽  
Rochdi Merzouki
Keyword(s):  
Energy Consumption ◽  
Mobile Robots ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Wheeled Mobile Robots ◽  
Optimal Energy ◽  
Optimal Trajectory Planning
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