Abstract
We present an online trajectory optimization method and software platform applicable to complex humanoid robots performing challenging tasks such as getting up from an arbitrary pose on the ground and recovering from large disturbances using dexterous acrobatic maneuvers. The resulting behaviors, illustrated in the attached video, are computed only 7 × slower than real time, on a standard PC. The video also shows results on the acrobot problem, planar swimming and one-legged hopping. These simpler problems can already be solved in real time, without pre-computing anything.
Keywords
Humanoid robotTrajectoryComputer scienceRobotTrajectory optimizationSoftwarePlanarArtificial intelligenceComputer visionSimulationComputer graphics (images)
Affiliated Institutions
Related Publications
Learning agile and dynamic motor skills for legged robots
A method for learning agile control policies uses simulated data to enable precise, efficient movements in a complex physical robot.
A comparison of single-cell trajectory inference methods
Trajectory inference approaches analyze genome-wide omics data from thousands of single cells and computationally infer the order of these cells along developmental trajectories...
Publication Info
- Year
- 2012
- Type
- article
- Citations
- 740
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
740
OpenAlex
Cite This
Yuval Tassa,
Tom Erez,
Emanuel Todorov
(2012).
Synthesis and stabilization of complex behaviors through online trajectory optimization.
.
https://doi.org/10.1109/iros.2012.6386025
Identifiers
- DOI
- 10.1109/iros.2012.6386025