scholarly journals A real-time trajectory planning method for enhanced path-tracking performance of serial manipulators

2021 ◽  
Vol 156 ◽  
pp. 104152
Author(s):  
Marco Faroni ◽  
Manuel Beschi ◽  
Antonio Visioli ◽  
Nicola Pedrocchi
Keyword(s):  
Real Time ◽  
Trajectory Planning ◽  
Path Tracking ◽  
Planning Method ◽  
Tracking Performance ◽  
Serial Manipulators

An optimal trajectory planning method for path tracking of industrial robots

Robotica ◽  
2018 ◽  
Vol 37 (3) ◽  
pp. 502-520 ◽  
Author(s):  
Xianxi Luo ◽  
Shuhui Li ◽  
Shubo Liu ◽  
Guoquan Liu
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimal Path ◽  
Path Tracking ◽  
Industrial Robots ◽  
Planning Method ◽  
Coordinate Frame ◽  
Optimization Approach ◽  
Cartesian Coordinate ◽  
Optimal Trajectory Planning

SUMMARYThis paper presents an optimal trajectory planning method for industrial robots. The paper specially focuses on the applications of path tracking. The problem is to plan the trajectory with a specified geometric path, while allowing the position and orientation of the path to be arbitrarily selected within the specific ranges. The special contributions of the paper include (1) an optimal path tracking formulation focusing on the least time and energy consumption without violating the kinematic constraints, (2) a special mechanism to discretize a prescribed path integration for segment interpolation to fulfill the optimization requirements of a task with its constraints, (3) a novel genetic algorithm (GA) optimization approach that transforms a target path to be tracked as a curve with optimal translation and orientation with respect to the world Cartesian coordinate frame, (4) an integration of the interval analysis, piecewise planning and GA algorithm to overcome the challenges for solving the special trajectory planning and path tracking optimization problem. Simulation study shows that it is an insufficient condition to define a trajectory just based on the consideration that each point on the trajectory should be reachable. Simulation results also demonstrate that the optimal trajectory for a path tracking problem can be obtained effectively and efficiently using the proposed method. The proposed method has the properties of broad adaptability, high feasibility and capability to achieve global optimization.

A stepping gait trajectory design based on hip height variation of swing leg for the balance of lower extremity exoskeleton

2019 ◽  
Vol 47 (2) ◽  
pp. 281-292
Author(s):  
Canjun Yang ◽  
Hansong Wang ◽  
Qihang Zhu ◽  
Xiangzhi Liu ◽  
Wei Yang ◽  
...  
Keyword(s):  
Lower Extremity ◽  
Real Time ◽  
Trajectory Planning ◽  
Planning Method ◽  
Trajectory Design ◽  
Height Variation ◽  
Content Type ◽  
Time Stepping ◽  
The Poor ◽  
Cord Injury

Purpose Lower extremity exoskeletons have drawn much attention recently due to their potential ability to help the stroke and spinal cord injury patients to regain the ability of walking. However, the balance of the human-exoskeleton system (HES) remains a big challenge. Usually, patients use crutches to keep balance when they wear exoskeleton. However, the balance depends greatly on the patient's balance ability and will be inevitably poor occasionally, which often causes the landing in advance of HES. The purpose of this paper is to propose a real-time stepping gait trajectory planning method based on the hip height variation of the swing leg to solve the problem. Design/methodology/approach The hip height of the swing leg was analyzed and measured. The simulation with MATLAB and the experimental test with the prototype of the proposed gait were conducted to verify its feasibility. Findings With the proposed method, HES can achieve successful step even when the balance kept by crutches is poor. Research limitations/implications Instead of actively avoiding the poor balance due to the instability caused by gravity, the method just modifies the stepping gait passively to avoid the landing in advance when the poor balance appears. In addition, it may not work well when the balance is too poor. Moreover, the proposed gait is just used in the initial stage of rehabilitation training. Besides, the step length of the gait must be limited for comfort. Originality/value A real-time stepping gait trajectory planning method based on the hip height variation of the swing leg is first proposed and its feasibility to avoid the landing in advance when the balance kept by the crutches is poor has been preliminary verified.

scholarly journals A Hierarchical Autonomous Driver for a Racing Car: Real-Time Planning and Tracking of the Trajectory

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6008
Author(s):  
Margherita Montani ◽  
Leandro Ronchi ◽  
Renzo Capitani ◽  
Claudio Annicchiarico
Keyword(s):  
Real Time ◽  
Trajectory Planning ◽  
Vehicle Dynamics ◽  
Trajectory Optimization ◽  
Computational Cost ◽  
Path Tracking ◽  
Driver Model ◽  
Current Scenario ◽  
Optimum Model ◽  
Time Planning

The aim of this study was to develop trajectory planning that would allow an autonomous racing car to be driven as close as possible to what a driver would do, defining the most appropriate inputs for the current scenario. The search for the optimal trajectory in terms of lap time reduction involves the modeling of all the non-linearities of the vehicle dynamics with the disadvantage of being a time-consuming problem and not being able to be implemented in real-time. However, to improve the vehicle performances, the trajectory needs to be optimized online with the knowledge of the actual vehicle dynamics and path conditions. Therefore, this study involved the development of an architecture that allows an autonomous racing car to have an optimal online trajectory planning and path tracking ensuring professional driver performances. The real-time trajectory optimization can also ensure a possible future implementation in the urban area where obstacles and dynamic scenarios could be faced. It was chosen to implement a local trajectory planning based on the Model Predictive Control(MPC) logic and solved as Linear Programming (LP) by Sequential Convex Programming (SCP). The idea was to achieve a computational cost, 0.1 s, using a point mass vehicle model constrained by experimental definition and approximation of the car’s GG-V, and developing an optimum model-based path tracking to define the driver model that allows A car to follow the trajectory defined by the planner ensuring a signal input every 0.001 s. To validate the algorithm, two types of tests were carried out: a Matlab-Simulink, Vi-Grade co-simulation test, comparing the proposed algorithm with the performance of an offline motion planning, and a real-time simulator test, comparing the proposed algorithm with the performance of a professional driver. The results obtained showed that the computational cost of the optimization algorithm developed is below the limit of 0.1 s, and the architecture showed a reduction of the lap time of about 1 s compared to the offline optimizer and reproducibility of the performance obtained by the driver.

An improved robot trajectory planning method considering torque saturation and modeling errors

2020 ◽  
Vol 44 (2) ◽  
pp. 213-227
Author(s):  
Yadong Ding ◽  
Yaoyao Wang ◽  
Feng Ju ◽  
Bai Chen
Keyword(s):  
Trajectory Planning ◽  
Dynamic Modelling ◽  
Parameter Estimate ◽  
Path Tracking ◽  
Tracking Performance ◽  
Joint Torques ◽  
Motion Time ◽  
Modeling Errors ◽  
Time Optimal ◽  
On Line

Time-optimal trajectory planning algorithms have been widely adopted to minimize the motion time by exploiting the dynamics and joint allowable torques of a robotic manipulator. However, the actual joint torques may exceed the joint allowable torques because of modelling errors or disturbances in the control system. When the torque limit is added for actuator safety, the controller will have no margin to deal with modeling errors or disturbances, which may lead to large path tracking errors. An on-line trajectory time scaling method called path velocity controller can improve path tracking performance by modifying the path velocity when torque saturation occurs. However, the path velocity controller is based on a feedforward or computed torque controller, so the dynamic modelling errors will worsen the path tracking performance. In addition, the motion time may also be increased because the dynamic modelling errors could result in longer duration time of torque saturation. To further improve the path tracking performance of a path velocity controller, a path velocity controller with an on-line parameter estimate mechanism is proposed. The simulation results show that the proposed method can achieve a better path tracking performance and shorter motion time.

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