Model Predictive Control of Robots

Humanoid motion generation in a world of stairs

Consider the problem of generating humanoid motions in an environment consisting of horizontal patches located at different heights (world of stairs). To this end, the paper proposes an integrated scheme which combines footstep planning and gait generation. In particular, footsteps are produced by...
From Walking to Running: 3D Humanoid Gait Generation via MPC

We present a real-time algorithm for humanoid 3D walking and/or running based on a Model Predictive Control (MPC) approach. The objective is to generate a stable gait that replicates as closely as possible a footstep plan, i.e., a sequence of candidate footstep positions and orientations with...
An Intrinsically Stable MPC Approach for Anti-Jackknifing Control of Tractor-Trailer Vehicles

Tractor-trailer vehicles are affected by jackknifing, a phenomenon that consists in the divergence of the trailer hitch angle and ultimately causes the vehicle to fold up. For the case of backward motions, in which jackknifing can occur at any speed, we present a control method that drives the...
Task-Oriented Generation of Stable Motions for Wheeled Inverted Pendulum Robots

We present a whole-body control architecture for the generation of stable task-oriented motions in Wheeled Inverted Pendulum (WIP) robots. Controlling WIP systems is challenging because the successful execution of tasks is subordinate to the ability to maintain balance. Our feedback control...
Bayesian Neural Network Modeling and Hierarchical MPC for a Tendon-Driven Surgical Robot with Uncertainty Minimization

In order to guarantee precision and safety in robotic surgery, accurate models of the robot and proper control strategies are needed. Bayesian Neural Networks (BNN) are capable of learning complex models and provide information about the uncertainties of the learned system. Model Predictive Control...
Enforcing Constraints over Learned Policies via Nonlinear MPC: Application to the Pendubot

In recent years Reinforcement Learning (RL) has achieved remarkable results. Nonetheless RL algorithms prove to be unsuccessful in robotics applications where constraints satisfaction is involved, e.g. for safety. In this work we propose a control algorithm that allows to enforce constraints over a...
Robust MPC-Based Gait Generation in Humanoids

We introduce a robust gait generation framework for humanoid robots based on our Intrinsically Stable Model Predictive Control (IS-MPC) scheme, which features a stability constraint to guarantee internal stability. With respect to the original version, the new framework adds multiple components...
Enforcing Constraints over Learned Policies via Nonlinear MPC: Application to the Pendubot
Anti-Jackknifing Control of Tractor-Trailer Vehicles via Intrinsically Stable MPC
An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay