Trajectory Optimization With Implicit Hard Contacts

We present a contact invariant trajectory optimization formulation to synthesize motions for legged robotic systems. The method is capable of finding optimal trajectories subject to whole-body dynamics with hard contacts. Contact switches are determined automatically. We make use of concepts from bi...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE robotics and automation letters Ročník 3; číslo 4; s. 3316 - 3323
Hlavní autoři: Carius, Jan, Ranftl, Rene, Koltun, Vladlen, Hutter, Marco
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Computer simulation
Dynamics
Force
Legged locomotion
legged robots
Optimal control
Optimization
optimization and optimal control
Switches
Synthesis
System dynamics
Trajectory
Trajectory optimization
ISSN:2377-3766, 2377-3766
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:We present a contact invariant trajectory optimization formulation to synthesize motions for legged robotic systems. The method is capable of finding optimal trajectories subject to whole-body dynamics with hard contacts. Contact switches are determined automatically. We make use of concepts from bilevel optimization to find gradients of the system dynamics including the constraint forces and subsequently solve the optimal control problem with the unconstrained iLQR algorithm. Our formulation achieves fast computation times and scales well with the number of contact points. The physical correctness of the produced trajectories is verified through experiments in simulation and on real hardware. We showcase our method on a single-legged hopper for which jumping and forward hopping motions are synthesized with an arbitrary number of contact switches. The jumping trajectories can be tracked on the robot and allow it to safely liftoff and land.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2018.2852785