TY - JOUR
T1 - Legged Elastic Multibody Systems
T2 - Adjusting Limit Cycles to Close-To-Optimal Energy Efficiency
AU - Stratmann, Philipp
AU - Lakatos, Dominic
AU - Ozparpucu, Mehmet C.
AU - Albu-Schaffer, Alin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/4
Y1 - 2017/4
N2 - Compliant elements in robotic systems can strongly increase the energy efficiency of highly dynamic periodic motions with large energy consumption such as jumping. Their control is a challenging task for multijoint systems. Typical control algorithms are model-based and thus fail to adjust to unexpected mechanical environments or make limited use of mechanical resonance properties. Here, we apply numerical optimal control theory to demonstrate that close-To-optimal energy-efficient movements can be induced from a one-dimensional (1-D) submanifold in jumping systems that show nonlinear hybrid dynamics. Linear weights transform sensory information into this 1-D controller space and reverse transform 1-D motor signals back into the multidimensional joint space. In Monte-Carlo-based simulations and experiments, we show that an algorithm that we derived previously can extract these weights online from sensory information about joint positions of a moving system. The algorithm is computationally cheap, modular, and adjusts to varying mechanical conditions. Our results demonstrate that it reduces the problem of energy-efficient control of multiple compliant joints that move with high synchronicity to a low-dimensional task.
AB - Compliant elements in robotic systems can strongly increase the energy efficiency of highly dynamic periodic motions with large energy consumption such as jumping. Their control is a challenging task for multijoint systems. Typical control algorithms are model-based and thus fail to adjust to unexpected mechanical environments or make limited use of mechanical resonance properties. Here, we apply numerical optimal control theory to demonstrate that close-To-optimal energy-efficient movements can be induced from a one-dimensional (1-D) submanifold in jumping systems that show nonlinear hybrid dynamics. Linear weights transform sensory information into this 1-D controller space and reverse transform 1-D motor signals back into the multidimensional joint space. In Monte-Carlo-based simulations and experiments, we show that an algorithm that we derived previously can extract these weights online from sensory information about joint positions of a moving system. The algorithm is computationally cheap, modular, and adjusts to varying mechanical conditions. Our results demonstrate that it reduces the problem of energy-efficient control of multiple compliant joints that move with high synchronicity to a low-dimensional task.
KW - Compliance and impedance control
KW - optimization and optimal control
KW - redundant robots
UR - http://www.scopus.com/inward/record.url?scp=85058997065&partnerID=8YFLogxK
U2 - 10.1109/LRA.2016.2633580
DO - 10.1109/LRA.2016.2633580
M3 - Article
AN - SCOPUS:85058997065
SN - 2377-3766
VL - 2
SP - 436
EP - 443
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 2
M1 - 7762857
ER -