Variable impedance MPC formulations contain a false feasibility gap between the assumed stiffness set and the set realizable under actuator dynamics, with an analytical threshold below which no command works.
Agile maneuvers in legged robots: A predictive control approach
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
Planning and execution of agile locomotion maneuvers have been a longstanding challenge in legged robotics. It requires to derive motion plans and local feedback policies in real-time to handle the nonholonomy of the kinetic momenta. To achieve so, we propose a hybrid predictive controller that considers the robot's actuation limits and full-body dynamics. It combines the feedback policies with tactile information to locally predict future actions. It converges within a few milliseconds thanks to a feasibility-driven approach. Our predictive controller enables ANYmal robots to generate agile maneuvers in realistic scenarios. A crucial element is to track the local feedback policies as, in contrast to whole-body control, they achieve the desired angular momentum. To the best of our knowledge, our predictive controller is the first to handle actuation limits, generate agile locomotion maneuvers, and execute optimal feedback policies for low level torque control without the use of a separate whole-body controller.
citation-role summary
citation-polarity summary
fields
cs.RO 2years
2026 2verdicts
CONDITIONAL 2roles
background 1polarities
background 1representative citing papers
Lifting non-conservative, actuated, and contact-constrained robot dynamics into an exactly symplectic phase-space map yields state-of-the-art out-of-distribution autoregressive rollout error at low parameter and FLOP cost.
citing papers explorer
-
False Feasibility in Variable Impedance MPC for Legged Locomotion
Variable impedance MPC formulations contain a false feasibility gap between the assumed stiffness set and the set realizable under actuator dynamics, with an analytical threshold below which no command works.
-
CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts
Lifting non-conservative, actuated, and contact-constrained robot dynamics into an exactly symplectic phase-space map yields state-of-the-art out-of-distribution autoregressive rollout error at low parameter and FLOP cost.