23 research outputs found
Actuation-Aware Simplified Dynamic Models for Robotic Legged Locomotion
In recent years, we witnessed an ever increasing number of successful hardware implementations of motion planners for legged robots. If one common property is to be identified among these real-world applications, that is the ability of online planning.
Online planning is forgiving, in the sense that it allows to relentlessly compensate for external disturbances of whatever form they might be, ranging from unmodeled dynamics to external pushes or unexpected obstacles and, at the same time, follow user commands. Initially replanning was restricted only to heuristic-based planners that exploit the low computational effort of simplified dynamic models. Such models deliberately only capture the main dynamics of the system, thus leaving to the controllers the issue of anchoring the desired trajectory to the whole body model of the robot. In recent years, however, we have seen a number of new approaches attempting to increase the accuracy of the dynamic formulation without trading-off the computational efficiency of simplified models.
In this dissertation, as an example of successful hardware implementation of heuristics and simplified model-based locomotion, I describe the framework that I developed for the generation of an omni-directional bounding gait for the HyQ quadruped robot. By analyzing the stable limit cycles for the sagittal dynamics and the Center of Pressure (CoP) for the lateral stabilization, the described locomotion framework is able to achieve a stable bounding while adapting to terrains of mild roughness and to sudden changes of the user desired linear and angular velocities.
The next topic reported and second contribution of this dissertation is my effort to formulate more descriptive simplified dynamic models, without trading off their computational efficiency, in order to extend the navigation capabilities of legged robots to complex geometry environments. With this in mind, I investigated the possibility of incorporating feasibility constraints in these template models and, in particular, I focused on the joint torques limits which are usually neglected at the planning stage.
In this direction, the third contribution discussed in this thesis is the formulation of the so called actuation wrench polytope (AWP), defined as the set of feasible wrenches that an articulated robot can perform given its actuation limits. Interesected with the contact wrench cone (CWC), this yields a new 6D polytope that we name feasible wrench polytope (FWP), defined as the set of all wrenches that a legged robot can realize given its actuation capabilities and the friction constraints. Results are reported where, thanks to efficient computational geometry algorithms and to appropriate approximations, the FWP is employed for a one-step receding horizon optimization of center of mass trajectory and phase durations given a predefined step sequence on rough terrains.
For the sake of reachable workspace augmentation, I then decided to trade off the generality of the FWP formulation for a suboptimal scenario in which a quasi-static motion is assumed.
This led to the definition of the, so called, local/instantaneous actuation region and of the global actuation/feasible region. They both can be seen as different variants of 2D linear subspaces orthogonal to gravity where the robot is guaranteed to place its own center of mass while being able to carry its own body weight given its actuation capabilities. These areas can be intersected with the well known frictional support region, resulting in a 2D linear feasible region, thus providing an intuitive tool that enables the concurrent online optimization of actuation consistent CoM trajectories and target foothold locations on rough terrains
An Efficient Paradigm for Feasibility Guarantees in Legged Locomotion
Developing feasible body trajectories for legged systems on arbitrary
terrains is a challenging task. Given some contact points, the trajectories for
the Center of Mass (CoM) and body orientation, designed to move the robot, must
satisfy crucial constraints to maintain balance, and to avoid violating
physical actuation and kinematic limits. In this paper, we present a paradigm
that allows to design feasible trajectories in an efficient manner. In
continuation to our previous work, we extend the notion of the 2D feasible
region, where static balance and the satisfaction of actuation limits were
guaranteed, whenever the projection of the CoM lies inside the proposed
admissible region. We here develop a general formulation of the improved
feasible region to guarantee dynamic balance alongside the satisfaction of both
actuation and kinematic limits for arbitrary terrains in an efficient manner.
To incorporate the feasibility of the kinematic limits, we introduce an
algorithm that computes the reachable region of the CoM. Furthermore, we
propose an efficient planning strategy that utilizes the improved feasible
region to design feasible CoM and body orientation trajectories. Finally, we
validate the capabilities of the improved feasible region and the effectiveness
of the proposed planning strategy, using simulations and experiments on the HyQ
robot and comparing them to a previously developed heuristic approach. Various
scenarios and terrains that mimic confined and challenging environments are
used for the validation.Comment: 17 pages, 13 figures, submitted to Transaction on Robotic
Optimizing Dynamic Trajectories for Robustness to Disturbances Using Polytopic Projections
This paper focuses on robustness to disturbance forces and uncertain
payloads. We present a novel formulation to optimize the robustness of dynamic
trajectories. A straightforward transcription of this formulation into a
nonlinear programming problem is not tractable for state-of-the-art solvers,
but it is possible to overcome this complication by exploiting the structure
induced by the kinematics of the robot. The non-trivial transcription proposed
allows trajectory optimization frameworks to converge to highly robust dynamic
solutions. We demonstrate the results of our approach using a quadruped robot
equipped with a manipulator.Comment: Final accepted version to the IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS) 2020. Supplementary video:
https://youtu.be/vDesP7IpTh
Feasible Wrench Set Computation for Legged Robots
During locomotion, legged robots interact with the ground by sequentially
establishing and breaking contact. The interaction wrenches that arise from
contact are used to steer the robot Center of Mass (CoM) and reject
perturbations that make the system deviate from the desired trajectory and
often make them fall. The feasibility of a given control target (desired CoM
wrench or acceleration) is conditioned by the contact point distribution,
ground friction, and actuation limits. In this work, we develop a method to
compute the set of feasible wrenches that a legged robot can exert on its CoM
through contact. The presented method can be used with any amount of
non-co-planar contacts and takes into account actuation limits and limitations
based on an inelastic contact model with Coulomb friction. This is exemplified
with a planar biped model standing with the feet at different heights.
Exploiting assumptions from the contact model, we explain how to compute the
set of wrenches that are feasible on the CoM when the contacts remain in
position as well as the ones that are feasible when some of the contacts are
broken. Therefore, this method can be used to assess whether a switch in
contact configuration is feasible while achieving a given control task.
Furthermore, the method can be used to identify the directions in which the
system is not actuated (i.e. a wrench cannot be exerted in those directions).
We show how having a joint be actuated or passive can change the non-actuated
wrench directions of a robot at a given pose using a spatial model of a
lower-extremity exoskeleton. Therefore, this method is also a useful tool for
the design phase of the system. This work presents a useful tool for the
control and design of legged systems that extends on the current state of the
art.Comment: \c{opyright} 2022 IEEE. Personal use of this material is permitted.
Permission from IEEE must be obtained for all other uses, in any current or
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this work in other work
Optimisation of Body-ground Contact for Augmenting Whole-Body Loco-manipulation of Quadruped Robots
Legged robots have great potential to perform loco-manipulation tasks, yet it
is challenging to keep the robot balanced while it interacts with the
environment. In this paper we study the use of additional contact points for
maximising the robustness of loco-manipulation motions. Specifically,
body-ground contact is studied for enhancing robustness and manipulation
capabilities of quadrupedal robots. We propose to equip the robot with prongs:
small legs rigidly attached to the body which ensure body-ground contact occurs
in controllable point-contacts. The effect of these prongs on robustness is
quantified by computing the Smallest Unrejectable Force (SUF), a measure of
robustness related to Feasible Wrench Polytopes. We apply the SUF to assess the
robustness of the system, and propose an effective approximation of the SUF
that can be computed at near-real-time speed. We design a hierarchical
quadratic programming based whole-body controller that controls stable
interaction when the prongs are in contact with the ground. This novel concept
of using prongs and the resulting control framework are all implemented on
hardware to validate the effectiveness of the increased robustness and newly
enabled loco-manipulation tasks, such as obstacle clearance and manipulation of
a large object
Robustness to external disturbances for legged robots using dynamic trajectory optimisation
In robotics, robustness is an important and desirable attribute of any system, from
perception to planning and control. Robotic systems need to handle numerous factors
of uncertainty when they are deployed, and the more robust a method is, the fewer
chances there are of something going wrong. In planning and control, being robust
is crucial to deal with uncertain contact timings and positions, mismatches in the
dynamics model of the system, noise in the sensor readings and communication
delays. In this thesis, we focus on the problem of dealing with uncertainty and
external disturbances applied to the robot.
Reactive robustness can be achieved at the control stage using a variety of control
schemes. For example, model predictive control approaches are robust against external
disturbances thanks to the online high-frequency replanning of the motion being
executed. However, taking robustness into account in a proactive way, i.e., during the
planning stage itself, enables the adoption of kinematic configurations that allow the
system as a whole to better deal with uncertainty and disturbances.
To this end, we propose a novel trajectory optimisation framework for robotic
systems, ranging from fixed-base manipulators to legged robots, such as humanoids
or quadrupeds equipped with arms. We tackle the problem from a first-principles
perspective, and define a robustness metric based on the robot’s capabilities, such as
the torques available to the system (considering actuator torque limits) and contact
stability constraints. We compare our results with other existing approaches and,
through simulation and experiments on the real robot, we show that our method is
able to plan trajectories that are more robust against external disturbances
Déplacement d'un mannequin virtuel dans un environnement encombré : simulation de mouvement en intégrant les contraintes d'équilibre
This thesis was carried out in collaboration and co-funding of LSI of CEA/LIST and LBMC of IFSTTAR. The aim of the thesis was to study and develop a method for simulating the movement of a virtual manikin (VM) in a cluttered environment based on a priori knowledge. This thesis presents firstly motion capture (MoCap) experiments. The recorded data were analyzed to define some principles on human motion in cluttered environments. We then propose a general balance criterion and stability margin, based on a simplified model of VM. Then, we present a hierarchical framework that can generate and simulate dynamic movements of VM in a cluttered environment in three stages: a global trajectory of the center of mass (CoM) is generated at the global level to ensure balance in the VM's motion; then the trajectories of end-effectors (EE, ie feet, hands) and postures are generated locally under constraints of kinematics and collision avoidance; finally at the execution level, trajectories (CoM and EEs) and postures are used as references in a dynamic controller associated with VM so that the VM realizes the motion in a simulation. This framework is implemented in a car-ingress scenario in order to evaluate its performance and to suggest future improvementsCette thèse a été réalisée en collaboration et cofinancement impliquant le LSI du CEA/LIST et le LBMC de l'IFSTTAR. L'objectif de thèse était d'étudier et de développer une méthode pour simuler les mouvements d'un mannequin virtuel (MV) dans un environnement encombré en s'appuyant sur des connaissances a priori. L'étude présente, dans un premier temps, des expériences de capture de mouvement (MoCap). Les données enregistrées ont été analysées afin de définir quelques principes sur les mouvements humains dans des environnements encombrés. Nous proposons ensuite un critère général d'équilibre et une marge de stabilité, sur la base d'un modèle simplifié du MV. Puis, nous présentons un framework hiérarchique pouvant générer et simuler des mouvements dynamiques du MV dans un environnement encombré en trois étapes : une trajectoire globale du centre de masse (CoM) est générée au niveau global afin d'assurer l'équilibre du MV durant son mouvement; puis au niveau local, les trajectoires des organes terminaux (OT, i.e. pieds, mains) et les postures sont générées localement sous des contraintes cinématiques et d'évitement de collisions; enfin au niveau de l'exécution, les trajectoires (CoM et OTs) et les postures sont utilisées comme références dans un contrôleur dynamique associé au MV. Enfin, ce framework est mis en œuvre dans un scenario d'entrée dans un véhicule pour évaluer ses performances et proposer des améliorations future