Name
Abstract | ||
|---|---|---|
A resilient robotic system is capable of recovering the original function after some parts failed. This paper develops a general architecture of resilient robot in terms of physical components and their relationships. This architecture includes active joints and passive joints and adjustable links. The inclusion of passive joints and adjustable link can offer benefit not only on cost, but also on functionality. The architecture determines the configuration variations in terms of discrete variables, i.e., types of modules, assembly pattern of each module and continuous variables, i.e., length of links between two joints and the initial location of the base. The configuration synthesis is formulated as an optimization problem. Energy consumption and resilience is chosen as the objective function. The task-based kinematic and dynamic model is included as the constraints for the underactuated resilient robot that has active joints and passive joints. A genetic algorithm is employed to search for the optimal configuration. This approach is validated by a 3-DOF manipulator. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/AIM.2014.6878164 | AIM |
Keywords | Field | DocType |
design engineering,genetic algorithms,manipulator dynamics,manipulator kinematics,3-dof manipulator,active joints,adjustable links,configuration synthesis,configuration variations,continuous variables,degree-of-freedom,discrete variables,dynamic model,energy consumption,genetic algorithm,objective function,optimization problem,passive joints,resilient robot architecture,task-based kinematic model,underactuated resilient robotic systems,assembly,resilience,robot kinematics,degree of freedom,computer architecture | Architecture,Kinematics,Computer science,Control theory,Simulation,Control engineering,Underactuation,Robot,Energy consumption,Optimization problem,Genetic algorithm,Mobile manipulator | Conference |
ISSN | Citations | PageRank |
2159-6255 | 0 | 0.34 |
References | Authors | |
6 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tan Zhang | 1 | 210 | 18.19 |
| Changli Liu | 2 | 1 | 1.03 |
| Zhiqin Qian | 3 | 2 | 2.06 |
| Dan Zhang | 4 | 97 | 21.44 |
| Madan M. Gupta | 5 | 237 | 66.49 |
| wenjun zhang | 6 | 0 | 0.34 |