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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE robotics and automation letters Vol. 3; no. 4; pp. 3316 - 3323
Main Authors: Carius, Jan, Ranftl, Rene, Koltun, Vladlen, Hutter, Marco
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography: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