Extending the capabilities of robotic manipulators using trajectory optimization

Gallant, André; Gosselin, Clément

doi:10.1016/j.mechmachtheory.2017.09.016

Cited by 23 publications

(10 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The transformation of the state = [ , ] and the new state variables are stated as follows: (13). The state transformation makes the setting of the initial guess easier and therefore improves the success rate of the optimization dramatically.…”

Section: Actuation Constraintsmentioning

confidence: 99%

“…Nevertheless, the optimal control method is still the most common tool to solve this kind of problem, including indirect method based on Pontryagin's maximum principle and direct parameter optimization [6]. Besides, some other methods are also employed to solve the weight lifting problem of robot, such as trial-and-error learning method [10], redundancy resolution method [11,12], and polynomial-based trajectory optimization [13]. Thus, the optimal control method is a promising method to solve the weight lifting problem of variable stiffness actuated robot.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Weight Lifting Trajectory Optimization for Variable Stiffness Actuated Robot

Chen

Kong

2019

Complexity

View full text Add to dashboard Cite

Variable stiffness actuator is a new actuation of robot which is inspired by motor control of human arm. And it is promising way to exploit the human-like performance and human-like motion. However, due to the mechanical complexity and redundancy of the actuators, it is not trivial to control the variable stiffness actuated robot to perform a human-like motion. In this paper, the weight lifting problem with variable stiffness actuated robot is studied. Then, the original problem is formulated as a constrained optimal control problem and transformed as a general nonlinear programming problem with Gauss pseudospectral method. Simulation studies demonstrate the effectiveness of the proposed method compared with the iLQR approach. Furthermore, the simulations results are presented to show the influence of stiffness variation of variable stiffness actuators on the weight lifting problem.

show abstract

Section: Actuation Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Weight Lifting Trajectory Optimization for Variable Stiffness Actuated Robot

Chen

Kong

2019

Complexity

View full text Add to dashboard Cite

show abstract

“…In fact, assumption 1 can be seen in most related literature. 6,[27][28][29] In addition, this assumption is very important for analyzing the stability of the controlled robotic manipulators.…”

Section: Control Designmentioning

confidence: 99%

Neural network adaptive command filtered control of robotic manipulators with input saturation

Lin

Yang

2019

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

This paper investigates finite-time control of uncertain robotic manipulators with external disturbances by means of neural network control and backstepping technique. To solve the “explosion of terms” in traditional backstepping control, a second-order command filter is designed, and the virtual input and its first-order derivative can be obtained accurately in a finite time. The parameters of the neural network are updated by using the tracking error signals. The proposed controller can guarantee that the tracking error converges to a small region of the origin in some finite time. Finally, we give a simulation study to show the effectiveness of the proposed method.

show abstract

“…Steps 1 and 2 are computed before the execution of the motion. In static applications (i.e., without cooperation with other agents and in structured environments), they may be performed offline by using, for example, optimization-based algorithms [7,8,9] or by shaping high-order polynomials [10,11,12]. In the presence of dynamic obstacles and goals, they need to be performed just before the robot movement and computational time is therefore a key issue.…”

Section: Introductionmentioning

confidence: 99%

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

Faroni

Beschi

Visioli

et al. 2021

Mechanism and Machine Theory

View full text Add to dashboard Cite

Robotized assembly and manufacturing often require to modify the robot motion at runtime. When the primary constraint is to preserve the geometrical path as much as possible, it is convenient to scale the nominal trajectory in time to meet the robot constraints. Look-ahead techniques are computationally heavy, while non-look-ahead ones usually show poor performance in critical circumstances. This paper proposes a novel technique that can be embedded in non-look-ahead scaling algorithms to improve their performance. The proposed method takes into account the robot velocity, acceleration, and torque limits and modifies the velocity profile based on an approximated look-ahead criterion. To do this, it considers only the last point of a look-ahead window and, by linearizing the problem, it computes the maximum admissible robot velocity. The technique can be applied to existing trajectory scaling algorithms to confer look-ahead properties on them. Simulation and experimental results on a 6-degree-of-freedom manipulator show that the proposed method significantly reduces path-following errors.

show abstract

Extending the capabilities of robotic manipulators using trajectory optimization

Cited by 23 publications

References 20 publications

Weight Lifting Trajectory Optimization for Variable Stiffness Actuated Robot

Weight Lifting Trajectory Optimization for Variable Stiffness Actuated Robot

Neural network adaptive command filtered control of robotic manipulators with input saturation

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

Contact Info

Product

Resources

About