22 accepted papers
Mobile manipulators are designed to perform complex sequences of navigation and manipulation tasks in human-centered environments. While recent optimization-based methods such as Hierarchical Task Model Predictive Control (HTMPC) enable efficient multitask execution with strict task priorities, they…
Omnidirectional robots can be realized using Mecanum wheels or using a suitable arrangement of conventional steerable wheels. The latter group, known as omnidirectional steerable wheeled mobile robots (SWMRs), are known to have a lower cost with respect to the former, and to be more robust thanks to
We propose an effective whole-body MPC controller for locomotion of humanoid robots. Our method generates motions using the full kinematics, allowing it to account for joint limits and to exploit upper-body motions to reject disturbances. Each MPC iteration solves a single QP that considers the inte…
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Human-like</i> trajectory generation and footstep planning represent challenging problems in humanoid robotics. Recently, research in computer graphics investigated machine-learning methods for characte
In most MPC-based schemes used for humanoid gait generation, simple Quadratic Programming (QP) problems are considered for real-time implementation. Since these only allow for convex constraints, the generated gait may be conservative. In this paper we focus on the non-convex reachable region of the…
We present an iterative approach for planning and controlling motions of underactuated robots with uncertain dynamics. At its core, there is a learning process which estimates the perturbations induced by the model uncertainty on the active and passive degrees of freedom. The generic iteration of th
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 approach…
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
The feasibility region of a Model Predictive Control (MPC) algorithm is the subset of the state space in which the constrained optimization problem to be solved is feasible. In our recent Intrinsically Stable MPC (IS-MPC) method for humanoid gait generation, feasibility means being able to satisfy t
This article presents a novel algorithm for blending human inputs and automatic controller commands, guaranteeing safety in mixed-initiative interactions between humans and quadrotors. The algorithm is based on nonlinear model predictive control (NMPC) and involves using the state solution to assess
Consider the problem of planning collision-free motions for a robot that is assigned a soft task constraint, i.e., a desired path in task space with an associated error tolerance. To this end, we propose an opportunistic planning strategy in which two subplanners take turns in generating motions. Th
It is common knowledge that 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 backwards motion, in which jackknifing can also occur at low speeds, we present a co…
We present an extension of our previously proposed IS-MPC method for humanoid gait generation aimed at obtaining robust performance in the presence of disturbances. The considered disturbance signals vary in a range of known amplitude around a mid-range value that can change at each sampling time, b…
Walking gaits generated using Model Predictive Control (MPC) is widely used due to its capability to handle several constraints that characterize humanoid locomotion. The use of simplified models such as the Linear Inverted Pendulum allows to perform computations in real-time, giving the robot the f…
We consider the problem of planning whole-body motions for humanoids that must execute loco-manipulation tasks, i.e., manipulation tasks that implicitly require a locomotion phase. The proposed planner builds a tree in configuration-time space by concatenating feasible, collision-free whole-body mot…
We consider a pursuit-evasion problem between humanoids in the presence of obstacles. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are st…
In this paper we present a real-time collision check algorithm based on the parallel computation capabilities of recent graphics card's GPUs. We show an effective application of the proposed algorithm to solve the task-constrained real-time motion planning problem for a redundant manipulator. We pro…
We consider a pursuit-evasion problem between humanoids. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are structurally identical, althoug…
One of the key problems in planning and control of redundant robots is the fast generation of controls when multiple tasks and constraints need to be satisfied. In the literature, this problem is classically solved by multi-task prioritized approaches, where the priority of each task is determined b…
We present a method for performing evasive motions with a humanoid robot. In the considered scenario, the robot is standing in a workspace, when a moving obstacle (e.g., a human, or another robot) enters its safety area and heads towards it; the humanoid must plan and execute in real-time a maneuver
This paper addresses the problem of generating whole-body motions for a humanoid robot that must execute a certain task in an environment containing obstacles. The assigned task trajectory is deformable, and the planner may exploit this feature for finding a solution. Our framework consists of two m
This paper addresses the motion planning problem in the presence of obstacles for underactuated robots that are assigned a geometric task. It is assumed that the robot is subject to kinematic (joint limits, joint velocity bounds) as well as dynamic (torque bounds) constraints. Building on our previo…