A framework trains keypoint detectors on inpainted markerless robot images and uses runtime inpainting plus UKF for robust vision-based control without models or calibration.
" * write output.state after.block = add.period write newline
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
Integrates iterative learning control with a torque library to enable high-precision adaptive locomotion on bipedal and quadrupedal robots, reducing tracking errors by up to 85% and achieving over 30x faster control rates.
An unsupervised Bayesian inference method with amortized variational inference detects coordinated inauthentic accounts on Twitter by clustering on account-level traits and shared narratives, substantially outperforming naive baselines and approaching supervised performance.
Soft growing robots map unknown 2D environments by characterizing collision deformations, building a geometry-based simulator, and using Monte Carlo sampling to select optimal deployments that approach ideal actions.
citing papers explorer
-
Utilizing Inpainting for Keypoint Detection for Vision-Based Control of Robotic Manipulators
A framework trains keypoint detectors on inpainted markerless robot images and uses runtime inpainting plus UKF for robust vision-based control without models or calibration.
-
Iteratively Learning Muscle Memory for Legged Robots to Master Adaptive and High Precision Locomotion
Integrates iterative learning control with a torque library to enable high-precision adaptive locomotion on bipedal and quadrupedal robots, reducing tracking errors by up to 85% and achieving over 30x faster control rates.
-
Unsupervised detection of coordinated information operations in the wild
An unsupervised Bayesian inference method with amortized variational inference detects coordinated inauthentic accounts on Twitter by clustering on account-level traits and shared narratives, substantially outperforming naive baselines and approaching supervised performance.
-
Linking Exteroception and Proprioception through Improved Contact Modeling for Soft Growing Robots
Soft growing robots map unknown 2D environments by characterizing collision deformations, building a geometry-based simulator, and using Monte Carlo sampling to select optimal deployments that approach ideal actions.