179 research outputs found
Planning and Control Strategies for Motion and Interaction of the Humanoid Robot COMAN+
Despite the majority of robotic platforms are still confined in controlled environments such as factories, thanks to the ever-increasing level of autonomy and the progress on human-robot interaction, robots are starting to be employed for different operations, expanding their focus from uniquely industrial to more diversified scenarios.
Humanoid research seeks to obtain the versatility and dexterity of robots capable of mimicking human motion in any environment. With the aim of operating side-to-side with humans, they should be able to carry out complex tasks without posing a threat during operations.
In this regard, locomotion, physical interaction with the environment and safety are three essential skills to develop for a biped.
Concerning the higher behavioural level of a humanoid, this thesis addresses both ad-hoc movements generated for specific physical interaction tasks and cyclic movements for locomotion. While belonging to the same category and sharing some of the theoretical obstacles, these actions require different approaches: a general high-level task is composed of specific movements that depend on the environment and the nature of the task itself, while regular locomotion involves the generation of periodic trajectories of the limbs.
Separate planning and control architectures targeting these aspects of biped motion are designed and developed both from a theoretical and a practical standpoint, demonstrating their efficacy on the new humanoid robot COMAN+, built at Istituto Italiano di Tecnologia.
The problem of interaction has been tackled by mimicking the intrinsic elasticity of human muscles, integrating active compliant controllers. However, while state-of-the-art robots may be endowed with compliant architectures, not many can withstand potential system failures that could compromise the safety of a human interacting with the robot. This thesis proposes an implementation of such low-level controller that guarantees a fail-safe behaviour, removing the threat that a humanoid robot could pose if a system failure occurred
Footstep Adjustment for Biped Push Recovery on Slippery Surfaces
Despite extensive studies on motion stabilization of bipeds, they still
suffer from the lack of disturbance coping capability on slippery surfaces. In
this paper, a novel controller for stabilizing a bipedal motion in its sagittal
plane is developed with regard to the surface friction limitations. By taking
into account the physical limitation of the surface in the stabilization trend,
a more advanced level of reliability is achieved that provides higher
functionalities such as push recovery on low-friction surfaces and prevents the
stabilizer from overreacting. The discrete event-based strategy consists of
modifying the step length and time period at the beginning of each footstep in
order to reestablish stability necessary conditions while taking into account
the surface friction limitation as a constraint to prevent slippage. Adjusting
footsteps to prevent slippage in confronting external disturbances is perceived
as a novel strategy for keeping stability, quite similar to human reaction. The
developed methodology consists of rough closed-form solutions utilizing
elementary math operations for obtaining the control inputs, allowing to reach
a balance between convergence and computational cost, which is quite suitable
for real-time operations even with modest computational hardware. Several
numerical simulations, including push recovery and switching between different
gates on low-friction surfaces, are performed to demonstrate the effectiveness
of the proposed controller. In correlation with human-gait experience, the
results also reveal some physical aspects favoring stability and the fact of
switching between gaits to reduce the risk of falling in confronting different
conditions.Comment: for associated simulation video, see https://youtu.be/BWzUgHGdl3
Swing-Leg Trajectory of Running Guinea Fowl Suggests Task-Level Priority of Force Regulation Rather than Disturbance Rejection
This study was funded by grant RGY0062/2010 of the Human Frontier Science Program (HFSP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
We show dynamic locomotion strategies for wheeled quadrupedal robots, which
combine the advantages of both walking and driving. The developed optimization
framework tightly integrates the additional degrees of freedom introduced by
the wheels. Our approach relies on a zero-moment point based motion
optimization which continuously updates reference trajectories. The reference
motions are tracked by a hierarchical whole-body controller which computes
optimal generalized accelerations and contact forces by solving a sequence of
prioritized tasks including the nonholonomic rolling constraints. Our approach
has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled
including the non-steerable wheels attached to its legs. We conducted
experiments on flat and inclined terrains as well as over steps, whereby we
show that integrating the wheels into the motion control and planning framework
results in intuitive motion trajectories, which enable more robust and dynamic
locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4
m/s and a reduction of the cost of transport by 83 % we prove the superiority
of wheeled-legged robots compared to their legged counterparts.Comment: IEEE Robotics and Automation Letter
Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot
Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming
increasingly important as the level of play rises. Competition around the ball is now decided in a
matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to
kick the ball.
It is common to see a discontinuity between walking and kicking where a robot will return to an
initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour
by developing a transition gait that morphs the walk directly into the kick back swing pose. The
solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot.
The solution we develop involves the design of a central pattern generator to allow for controlled
steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk
so that precise step length control can be activated when required. An open loop trajectory mapping
approach is taken to the walk that is stabilized statically through the use of a phase varying joint
holding torque technique. We also examine the basic princples of open loop walking, focussing on the
commonly overlooked frontal plane motion.
The act of kicking itself is explored both analytically and empirically, and solutions are provided
that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour
(process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate
and efficient in terms of speed of execution
From walking to running: robust and 3D humanoid gait generation via MPC
Humanoid robots are platforms that can succeed in tasks conceived for humans. From locomotion in unstructured environments, to driving cars, or working in industrial plants,
these robots have a potential that is yet to be disclosed in systematic every-day-life applications. Such a perspective, however, is opposed by the need of solving complex
engineering problems under the hardware and software point of view. In this thesis, we focus on the software side of the problem, and in particular on locomotion control. The operativity of a legged humanoid is subordinate to its capability of realizing a reliable locomotion. In many settings, perturbations may undermine the balance and make the robot fall. Moreover, complex and dynamic motions might be required by the context, as for instance it could be needed to start running or climbing stairs to achieve a certain location in the shortest time. We present gait generation schemes based on Model Predictive Control (MPC) that tackle both the problem of robustness and tridimensional dynamic motions. The proposed control schemes adopt the typical paradigm of centroidal MPC for reference motion generation, enforcing dynamic balance through the Zero Moment Point condition, plus a whole-body controller that maps the generated trajectories to joint commands. Each of the described predictive controllers also feature a so-called stability constraint, preventing the generation of diverging Center of Mass trajectories with respect to the Zero Moment Point. Robustness is addressed by modeling the humanoid as a Linear Inverted Pendulum and devising two types of strategies. For persistent perturbations, a way to use a disturbance observer and a technique for constraint tightening (to ensure robust constraint satisfaction) are presented. In the case of impulsive pushes instead, techniques for footstep and timing adaptation are introduced. The underlying approach is to interpret robustness as a MPC feasibility problem, thus aiming at ensuring the existence of a solution for the constrained optimization problem to be solved at each iteration in spite of the perturbations. This perspective allows to devise simple solutions to complex problems, favoring a reliable real-time implementation.
For the tridimensional locomotion, on the other hand, the humanoid is modeled as a Variable Height Inverted Pendulum. Based on it, a two stage MPC is introduced with particular emphasis on the implementation of the stability constraint. The overall result is a gait generation scheme that allows the robot to overcome relatively complex
environments constituted by a non-flat terrain, with also the capability of realizing running gaits. The proposed methods are validated in different settings: from conceptual simulations in Matlab to validations in the DART dynamic environment, up to experimental tests on the NAO and the OP3 platforms
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