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.

A Novel Algorithm for Time Optimal Trajectory Planning

2014 ◽  
Author(s):  
Mingxing Yuan ◽  
Bin Yao ◽  
Dedong Gao ◽  
Xiaocong Zhu ◽  
Qingfeng Wang
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
Problem Of Time ◽  
High Productivity ◽  
Hard Constraints ◽  
Time Optimal ◽  
Rate Optimization ◽  
Feed Rate Optimization ◽  
Optimal Trajectory Planning

Time optimal trajectory planning under various hard constraints plays a significant role in simultaneously meeting the requirements on high productivity and high accuracy in the fields of both machining tools and robotics. In this paper, the problem of time optimal trajectory planning is first formulated. A novel back and forward check algorithm is subsequently proposed to solve the minimum time feed-rate optimization problem. The basic idea of the algorithm is to search the feasible solution in the specified interval using the back or forward operations. Four lemmas are presented to illustrate the calculating procedure of optimal solution and the feasibility of the proposed algorithm. Both the elliptic curve and eight profile are used as case studies to verify the effectiveness of the proposed algorithm.

Time-Optimal Trajectory Planning of Cable-Driven Parallel Mechanisms for Fully Specified Paths With G1-Discontinuities

2015 ◽  
Vol 137 (7) ◽  
Author(s):  
Eric Barnett ◽  
Clément Gosselin
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Trajectory Generation ◽  
Optimal Solution ◽  
Test System ◽  
Parallel Robots ◽  
Parallel Mechanisms ◽  
Cable Tension ◽  
Time Optimal ◽  
Optimal Trajectory Planning

Time-optimal trajectory planning (TOTP) is a well-studied problem in robotics and manufacturing, which involves the minimization of the time required for the operation point of a mechanism to follow a path, subject to a set of constraints. A TOTP technique, designed for fully specified paths that include abrupt changes in direction, was previously introduced by the first author of this paper: an incremental approach called minimum-time trajectory shaping (MTTS) was used. In the current paper, MTTS is converted to a dynamic technique and adapted for use with cable-driven parallel robots, which exhibit cable tension and motor torque constraints. For many applications, cable tensions along a path are verified after trajectory generation, rather than imposed during trajectory generation. For the technique proposed in this paper, the cable-tension constraints are imposed directly and fully integrated with MTTS, during trajectory generation, thus maintaining a time-optimal solution. MTTS is applied to a test system and path, and compared to the bang–bang technique. With the same constraints, the results obtained with both techniques are found to be very close. However, MTTS can be applied to a wider variety of paths, and accepts constraints on jerk and total acceleration that would be difficult to apply using the bang–bang approach.

Time-Optimal Trajectory Planning of Cable-Driven Parallel Mechanisms for Fully-Specified Paths With G1 Discontinuities

2013 ◽  
Author(s):  
Eric Barnett ◽  
Clément Gosselin
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Trajectory Generation ◽  
Optimal Solution ◽  
Vertical Direction ◽  
Parallel Robots ◽  
Parallel Mechanisms ◽  
Time Optimal ◽  
Time Required ◽  
Optimal Trajectory Planning

Time-optimal trajectory planning (TOTP) is a well-studied problem in robotics and manufacturing, which involves the minimization of the time required for the operation point of a mechanism to follow a path, subject to a set of constraints. A TOTP technique, designed for fully-specified paths that include abrupt changes in direction, was previously introduced by the first author of this paper: an incremental approach called minimum-time trajectory shaping (MTTS) was used. In the current paper, MTTS is adapted for use with cable-driven parallel robots, which exhibit the additional constraint that all cable tensions remain positive along a path to be followed. For many applications, cable tensions along a path are verified after trajectory generation, rather than imposed during trajectory generation. For the technique proposed in this paper, the minimum-tension constraint is imposed directly and is fully integrated with MTTS, during trajectory generation, thus maintaining a time-optimal solution. This approach is relevant for cable-driven mechanism applications that involve high accelerations, particularly in the vertical direction.

L2-Norm Optimal Trajectory Planning for Mobile Ground Vehicles in a Dynamically Changing Environment with both “Hard” and “Soft” Obstacles

2011 ◽  
Vol 130-134 ◽  
pp. 339-342
Author(s):  
Jian Yang ◽  
Mi Dong
Keyword(s):  
Boundary Conditions ◽  
Trajectory Planning ◽  
Design Parameter ◽  
Optimal Trajectory ◽  
Kinematic Model ◽  
Optimal Solution ◽  
Planning Problem ◽  
Ground Vehicles ◽  
Operational Environment ◽  
Optimal Trajectory Planning

In this paper, the real-time trajectory planning problem is considered for a differential vehicles in a dynamically changing operational environment. Some obstacles in the environment are not known apriori, they are either static or moving, and classified to two types: “hard” obstacles that must be avoided, and “soft” obstacles that can be run over/through. The proposed method presents trajectories, satisfying boundary conditions and vehicle’s kinematic model, in terms of polynomials with one design parameter. With a cost function ofL2norm, an optimal feasible trajectory is analytically solved for “hard” obstacles. By relaxing the optimal solution, “soft” obstacles are prioritized to be bypassed or overcome. The proposed method offers an automatic and systematic way of handling obstacles.The simulation is used to illustrate the proposed algorithm.

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.

The Simulation and Analyses of Timing-Optimal Trajectory Planning for 6DOF Robot

2014 ◽  
Vol 716-717 ◽  
pp. 1555-1558
Author(s):  
Zhi Jian Gou
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
Global Search ◽  
Search Performance ◽  
Improved Genetic Algorithm ◽  
Genetic Operators ◽  
Optimal Trajectory Planning

The algorithm has been improved to the adaptive genetic operators and flow based on the basic theory of simple genetic algorithm and adopted elitism strategy to select the best individual for iterative operation. The improved genetic algorithm not only ensured better global search performance, but also improved the convergent speed. The optimal solution was obtained and simulated by the improved genetic algorithms under the kinematical constraints.

The Research of Timing-Optimal Trajectory Planning Based on Improved Genetic Algorithms

2013 ◽  
Vol 433-435 ◽  
pp. 562-565 ◽  
Author(s):  
Zhi Jian Gou
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
Search Performance ◽  
Improved Genetic Algorithm ◽  
Genetic Operators ◽  
Operation Process ◽  
Optimal Trajectory Planning

The algorithm has been improved to the adaptive genetic operators and flow based on the basic theory of simple genetic algorithm and adopted elitism strategy to select the best individual for iterative operation. Program the operation process in the MATLAB software. The improved genetic algorithm not only ensured better global search performance, but also improved the convergent speed. The optimal solution was obtained by the improved genetic algorithms under the kinematical constraints.

scholarly journals A Time Optimal Trajectory Planning Method for Double-Pendulum Crane Systems with Obstacle Avoidance

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Wa Zhang ◽  
He Chen ◽  
Haiyong Chen ◽  
WeiPeng Liu
Keyword(s):  
Obstacle Avoidance ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Planning Method ◽  
Double Pendulum ◽  
Time Optimal ◽  
Optimal Trajectory Planning

Optimal trajectory planning of robot manipulators in the presence of moving obstacles

2000 ◽  
Vol 35 (8) ◽  
pp. 1079-1094 ◽  
Author(s):  
Sezimária F.P. Saramago ◽  
Valder Steffen Junior
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Robot Manipulators ◽  
Moving Obstacles ◽  
Optimal Trajectory Planning
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