A framework using 3D Poisson Safety Functions creates a single CBF for full-body dynamic collision avoidance on manipulators, proven to guarantee safety from sampled points and validated on a 7-DOF arm.
Nonlinear model predictive control of robotic systems with control lyapunov functions
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
FORMULA integrates MPC with CLFs and neural network CBFs for distributed safe formation control in multi-robot systems.
citing papers explorer
-
Full-Body Dynamic Safety for Robot Manipulators: 3D Poisson Safety Functions for CBF-Based Safety Filters
A framework using 3D Poisson Safety Functions creates a single CBF for full-body dynamic collision avoidance on manipulators, proven to guarantee safety from sampled points and validated on a 7-DOF arm.
-
FORMULA: FORmation MPC with neUral barrier Learning for safety Assurance
FORMULA integrates MPC with CLFs and neural network CBFs for distributed safe formation control in multi-robot systems.