Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
Potential field methods and their inherent limitations for mobile robot navigation
4 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
VRA grounds discrete-time joint acceleration commands in voltage-constrained actuator physics to eliminate unrealizable accelerations and reduce oscillations in electric motor systems.
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.
A sequential convex programming method reformulates non-convex spacecraft pointing objectives into convex cardinality minimization problems to maximize science observation time during a comet flyby under dynamics and fault constraints.
citing papers explorer
-
Learning Dynamic Rope Manipulation Using Task-Level Iterative Learning Control
Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
-
VRA: Grounding Discrete-Time Joint Acceleration in Voltage-Constrained Actuation
VRA grounds discrete-time joint acceleration commands in voltage-constrained actuator physics to eliminate unrealizable accelerations and reduce oscillations in electric motor systems.
-
Constrained Whole-Body Tracking for Humanoid Robots
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.
-
Optimal Science-time Reorientation Policy for the Comet Interceptor Flyby via Sequential Convex Programming
A sequential convex programming method reformulates non-convex spacecraft pointing objectives into convex cardinality minimization problems to maximize science observation time during a comet flyby under dynamics and fault constraints.