Optimal control
Related papers: 20
About
Optimal control is a mathematical framework for computing input sequences or feedback policies that drive a dynamical system from an initial state to a desired goal while minimizing a cost function — such as time, energy, or control effort — subject to physical and operational constraints. In robotics and AI, it underpins a wide range of capabilities: planning time-optimal trajectories for manipulators, generating stable locomotion for humanoids, and synthesizing motion plans that respect actuator limits and safety constraints. Practical computational approaches include direct collocation, multiple shooting, and differential dynamic programming, supported by tools like CasADi. Optimal control also connects naturally to model predictive control, which re-solves the optimization online to handle disturbances, and to reinforcement learning, where it informs policy search and inverse cost-learning methods. Its importance lies in providing principled, mathematically rigorous tools for generating high-performance robot behavior — enabling systems to act efficiently and safely in complex, constrained environments while offering interpretable guarantees that purely data-driven methods often lack.
Top Researchers
Top Institutes
Top Cited Papers
CasADi: a software framework for nonlinear optimization and optimal control
Joel A.E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, Moritz Diehl
Citations: 3693 • 2018
Practical Methods for Optimal Control using Nonlinear Programming
JT Betts, Ilya Kolmanovsky
Citations: 1462 • 2002
Time-Optimal Control of Robotic Manipulators Along Specified Paths
J.E. Bobrow, Steven Dubowsky, J.S. Gibson
Citations: 1301 • 1985
CHOMP: Covariant Hamiltonian optimization for motion planning
Matt Zucker, Nathan Ratliff, Anca D. Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher M. Dellin, J. Andrew Bagnell, Siddhartha S Srinivasa
Citations: 738 • 2013
A direct method for trajectory optimization of rigid bodies through contact
Michael Posa, Cecilia Cantu, Russ Tedrake
Citations: 608 • 2013
An Introduction to Trajectory Optimization: How to Do Your Own Direct Collocation
Matthew Kelly
Citations: 547 • 2017
Time-Optimal Path Tracking for Robots: A Convex Optimization Approach
Diederik Verscheure, Bram Demeulenaere, Jan Swevers, Joris De Schutter, Moritz Diehl
Citations: 538 • 2009
Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations
Pierre-Brice Wieber
Citations: 515 • 2006
Acting under uncertainty: discrete Bayesian models for mobile-robot navigation
Anthony R. Cassandra, Leslie Pack Kaelbling, James Kurien
Citations: 468 • 2002
A Generalized Path Integral Control Approach to Reinforcement Learning
Evangelos A. Theodorou, Jonas Buchli, Stefan Schaal
Citations: 449 • 2010
Control-limited differential dynamic programming
Yuval Tassa, Nicolas Mansard, Emo Todorov
Citations: 441 • 2014
A new method for smooth trajectory planning of robot manipulators
Alessandro Gasparetto, V. Zanotto
Citations: 431 • 2006
From human to humanoid locomotion—an inverse optimal control approach
Katja Mombaur, Anh Truong, Jean‐Paul Laumond
Citations: 428 • 2009
Kinodynamic RRT*: Asymptotically optimal motion planning for robots with linear dynamics
Dustin J. Webb, Jur van den Berg
Citations: 412 • 2013
LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
Jur van den Berg, Pieter Abbeel, Ken Goldberg
Citations: 402 • 2011
Trajectory-Tracking Control of Mobile Robot Systems Incorporating Neural-Dynamic Optimized Model Predictive Approach
Zhijun Li, Jun Deng, Renquan Lu, Xu Yong, Jianjun Bai, Chun‐Yi Su
Citations: 399 • 2015
Smooth and time-optimal trajectory planning for industrial manipulators along specified paths
Daniela Constantinescu, Elizabeth A. Croft
Citations: 383 • 2000
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
Chelsea Finn, Sergey Levine, Pieter Abbeel
Citations: 370 • 2016
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
Lars Blackmore, Masahiro Ono, Askar Bektassov, Brian Williams
Citations: 342 • 2010
Fast Direct Multiple Shooting Algorithms for Optimal Robot Control
Moritz Diehl, H. G. Bock, Holger Diedam, Pierre-Brice Wieber
Citations: 337 • 2007