Dynamic Behavior and Motion Planning of a Robot Arm with Non-Rigid Transmission<sup>#</sup>

Brancati, Renato; Rossi, Cesare; Timpone, Francesco

doi:10.1080/15397730701606627

Cited by 11 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the global requirements of China lunar rover design, the parameters of the rover used for this paper are shown in Table 1. Then the control model can be established in Simulink to control the Adams model [29]. During the moon surface, the acceleration because of gravity is set to g/6.…”

Section: Simulation Resultsmentioning

confidence: 99%

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Guo

Zhang

et al. 2013

IET Intelligent Transport Systems

View full text Add to dashboard Cite

Path following is a main and fundamental task for future lunar rover autonomous navigation. This study adopts genetic algorithm (GA) to optimise the parameters of a path-following fuzzy controller designed for a six-wheel lunar rover. Considering the influences of the orientation deviation and its variation rate to the controller performance, two quantisation factors and one scale factor are utilised to limit both the input and output variables. However, it is difficult to manually achieve the proper factors because they are coupling themselves complicatedly. They are adjusted and modified automatically during the path-following process based on GA to achieve the auto-tradeoff the parameter and its control performance. Those parameters are coded using floating-point encoding scheme, respectively. The minimum tracking error and the angular velocity are taken as the target function. After several iterations of crossover and mutation, the best parameters are determined aiming at achieving lower path tracking error with small angular velocity. Simulation on different paths and comparisons with traditional fuzzy controller results show the designed controller with optimised parameters has better performance than the one with manually regulated parameters.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Guo

Zhang

et al. 2013

IET Intelligent Transport Systems

View full text Add to dashboard Cite

show abstract

“…In [13], a method of virtual work is described to obtain the system matrix while [14] determines the inertia profile using the method of kinetic energy. In [15], analytic equations were derived for a two-link flexible manipulator. However, these analytic approaches are cumbersome, complex, error-prone, and are not easily applicable.…”

Section: Introductionmentioning

confidence: 99%

Energy optimal point-to-point motion profile optimization

Oosterwyck

Vanbecelaere

Knaepkens

et al. 2022

Mechanics Based Design of Structures and Machines

View full text Add to dashboard Cite

Position-controlled systems driving repetitive tasks are of significant importance in industrial machinery. The electric actuators used in these systems are responsible for a large part of the global energy consumption, indicating that major savings can be made in this field. In this context, motion profile optimization is a very cost-effective solution as it allows for more energy-efficient machines without additional hardware investments or adaptions. In particular, mono-actuated mechanisms with position-dependent system properties have received considerable attention in literature. However, the current state-of-the-art methods often use unbounded design parameters to describe the motion profile. This both increases the computational complexity and hampers the search for a global optimum. In this paper, Chebyshev polynomials are used to describe the motion profile. Moreover, the exact bounds on the Chebyshev design parameters are derived. This both seriously reduces the computational complexity and limits the design space, allowing the application of a global optimizer such as the genetic algorithm. Experiments validate the added value of the chosen approach. In this study, it is found that the energy consumption can be reduced by 62.9% compared to a standard reference motion profile.

show abstract

“…A systematic approach for computing collision-free optimal trajectories for parallel robots needs to take into account different aspects, such as presence, size, and shape of obstacles; number of d.o.f.s that can be controlled at same time; movable ranges, maximum reachable velocities, accelerations, and jerks; control speed (clock rate), safety issues (Brancati et al, 2007;Yan et al, 2010).…”

Section: Collision-free Motion Planningmentioning

confidence: 99%

An Experimental Validation of Collision-Free Trajectories for Parallel Manipulators

Carbone

Gómez-Bravo

Selvi

2012

Mechanics Based Design of Structures and Machines

View full text Add to dashboard Cite

This article proposes a systematic approach for validating the trajectories generated by a motion planning method in presence of obstacles for parallel manipulators having less than 6 degrees of freedom (d.o.f.s). The planning algorithm is based on combining a quick random search algorithm together with an optimization method, which aims to obtain feasible and reliable trajectories. The validation approach uses a probabilistic method, which includes Kalman filtering of experimental data. Experimental tests have been carried out by operating a Cassino Parallel Manipulator (CaPaMan) prototype at LARM in Cassino. Results are reported and discussed to show the effectiveness of the proposed approach to generate and validate suitable collision-free trajectories for parallel manipulators.

show abstract

Dynamic Behavior and Motion Planning of a Robot Arm with Non-Rigid Transmission^#

Cited by 11 publications

References 5 publications

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Energy optimal point-to-point motion profile optimization

An Experimental Validation of Collision-Free Trajectories for Parallel Manipulators

Contact Info

Product

Resources

About

Dynamic Behavior and Motion Planning of a Robot Arm with Non-Rigid Transmission#

Cited by 11 publications

References 5 publications

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Parameter optimisation of path‐following fuzzy controller for a six‐wheel lunar rover

Energy optimal point-to-point motion profile optimization

An Experimental Validation of Collision-Free Trajectories for Parallel Manipulators

Contact Info

Product

Resources

About

Dynamic Behavior and Motion Planning of a Robot Arm with Non-Rigid Transmission^#