TY - GEN
T1 - Configuration synthesis of underactuated resilient robotic systems
AU - Zhang, Tan
AU - Liu, Changli
AU - Qian, Zhiqin
AU - Zhang, Dan
AU - Gupta, Madan M.
AU - Zhang, Wenjun
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84906686682&partnerID=8YFLogxK
U2 - 10.1109/AIM.2014.6878164
DO - 10.1109/AIM.2014.6878164
M3 - Conference article published in proceeding or book
AN - SCOPUS:84906686682
SN - 9781479957361
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 721
EP - 726
BT - AIM 2014 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2014
Y2 - 8 July 2014 through 11 July 2014
ER -