Integral control of humanoid balance (original) (raw)
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A momentum-based balance controller for humanoid robots on non-level and non-stationary ground
Autonomous Robots, 2012
Recent research suggests the importance of controlling rotational dynamics of a humanoid robot in balance maintenance and gait. In this paper, we present a novel balance strategy that controls both linear and angular momentum of the robot. The controller's objective is defined in terms of the desired momenta, allowing intuitive control of the balancing behavior of the robot. By directly determining the ground reaction force (GRF) and the center of pressure (CoP) at each support foot to realize the desired momenta, this strategy can deal with non-level and nonstationary grounds, as well as different frictional properties at each foot-ground contact. When the robot cannot realize the desired values of linear and angular momenta simultaneously, the controller attributes higher priority to linear momentum at the cost of compromising angular momentum. This creates a large rotation of the upper body, reminiscent of the balancing behavior of humans. We develop a computationally efficient method to optimize GRFs and CoPs at individual foot by sequentially solving two small-scale constrained linear least-squares problems. The balance strategy is demonstrated on a simulated humanoid robot under experiments such as recovery from unknown external pushes and balancing on non-level and moving supports.
Dynamic Balance Force Control for compliant humanoid robots
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010
This paper presents a model-based method, called Dynamic Balance Force Control (DBFC), for determining full body joint torques based on desired COM motion and contact forces for compliant humanoid robots. The center of mass (COM) dynamics are affected directly through contact force control to achieve stable balance. This idea is used to formulate DBFC considering the full rigid-body dynamics of the robot to produce desired contact forces. To achieve generic force control tasks, a virtual model controller, DBFC-VMC, is presented. Examples using this control are presented as results from simulation and experiments on a force-controlled humanoid robot.
Local-level control of a humanoid robot prototype with force-driven balance
2007 7th IEEE-RAS International Conference on Humanoid Robots, 2007
The recent trend of humanoid robotics research has been deeply influenced by concepts such as distributed architectures, local control, force interaction and emergence of coordinated motions. A hypothesis is that feedback control from several sensors, such as force sensors and inertial devices, and more advanced control algorithms will be a key issue for the next developments. In this paper, we discuss how these concepts have been applied to a custom low-cost humanoid platform developed for research purposes. The humanoid robot is equipped with a rich set of sensors enabling the evaluation of simple feedback rules used online to control the robot. A great focus has been given to a force-driven controller based on the Jacobian transpose. A kind of intermediate local-level controller is implemented based on force sensing, providing robust and adaptive behaviour. The proposed ideas and concepts are introduced and validated in several hardware experiments.
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010
We present a novel momentum-based method for maintaining balance of humanoid robots. By controlling the desired ground reaction force (GRF) and center of pressure (CoP) at each support foot, our method can naturally deal with non-level and non-stationary ground at each foot-ground contact, as well as different frictional properties. We do not make use of the net GRF and CoP which may be difficult or impossible to compute for non-level grounds. Our method minimizes the ankle torques during double support. We show the effectiveness of this new balance control method by simulating various experiments with a humanoid robot including maintaining balance when two feet are on separate moving supports with different inclinations and velocities.
This paper provides a theoretical and thorough experimental comparison of two distinct posture control approaches: a fully model-based control approach, and a biologically-inspired approach derived from human observations. While the robotic approach can easily be applied to balancing in 3D and multi-contact situations, the biologically inspired balancer works currently only in 2D but shows interesting robustness properties under time delays in the feedback loop. This is an important feature when considering the signal transmission and processing properties in the human sensorimotor system. Both controllers were evaluated in a series of experiments with a torque controlled humanoid robot. The paper concludes with some suggestions for the improvement of model-based balancing approaches in robotics.
Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014
Recently several hierarchical inverse dynamics controllers based on cascades of quadratic programs have been proposed for application on torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and real-time computation requirements can be problematic. In this contribution we present an experimental evaluation of these algorithms in the context of balance control for a humanoid robot. The presented experiments demonstrate the applicability of the approach under real robot conditions (i.e. model uncertainty, estimation errors, etc). We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. We implement a momentum-based balance controller which shows robust performance in face of unknown disturbances, even when the robot is standing on only one foot. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.
Humanoid Robot Balance Control Using the Spherical Inverted Pendulum Mode
Frontiers in Robotics and AI, 2015
Human beings are highly efficient in maintaining standing balance under the influence of different perturbations. However, biped humanoid robots are far from exhibiting similar skills. This is mainly due to the limitations in the current control and modeling techniques used in humanoid robots. Even though approaches using the Linear Inverted Pendulum Model and the Preview Control schemes have shown improved results, they still suffer from shortcomings in the overall generated motion. We propose here a model and control approach that aims to overcome the limiting assumptions in the LIPM models through using the ankle joint variables in modeling and control of the standing balance of the humanoid robot.
Model-Free Active Balancing for Humanoid Robots
Lecture Notes in Computer Science, 2009
To be practical, humanoid robots must be able to manoeuvre over a variety of flat and uneven terrains, at different speeds and with varying gaits and motions. This paper describes three balancingreflex algorithms (threshold control, PID control, and hybrid control) that were implemented on a real 8 DOF small humanoid robot equipped with a two-axis accelerometer sensor to study the capabilities and limitations of various balancing algorithms when combined with a single sensor. We term this approach a model-free approach, since it does not require a mathematical model of the underlying robot. Instead the controller attempts to recreate successful previous motions (so-called baseline motions). In our extensive tests, the basic threshold algorithm proves the most effective overall. All algorithms are able to balance for simple tasks, but as the balancing required becomes more complex (e.g. controlling multiple joints over uneven terrain), the need for more sophisticated algorithms becomes apparent.
One-Leg Stance of Humanoid Robot using Active Balance Control
ArXiv, 2021
The task of self-balancing is one of the most important tasks when developing humanoid robots. This paper proposes a novel external balance mechanism for humanoid robot to maintain sideway balance. First, a dynamic model of the humanoid robot with balance mechanism and its simplified model are introduced. Secondly, a backstepping-based control method is utilized to split the system into two sub-systems. Then, a minimum observer-based controller is used to control the first sub-system. Since the second sub-system has unknown parameters, a model reference adaptive controller (MRAC) is used to control it. The proposed design divides the walking and balancing into two separated tasks, allowing the walking control can be executed independently of the balancing control. Furthermore, the use of the balance mechanism ensures the humanoid robot’s hip movement does not exceed the threshold of a human when walking. Thus, making the overall pose of the humanoid robot looks more natural. An expe...
A Biomechanically Motivated Two-Phase Strategy for Biped Upright Balance Control
2005
Balance maintenance and upright posture recovery under unexpected environmental forces are key requirements for safe and successful co-existence of humanoid robots in normal human environments. In this paper we present a two-phase control strategy for robust balance maintenance under a force disturbance. The first phase, called the reflex phase, is designed to withstand the immediate effect of the force. The second phase is the recovery phase where the system is steered back to a statically stable "home" posture. The reflex control law employs angular momentum and is characterized by its counter-intuitive quality of "yielding" to the disturbance. The recovery control employs a general scheme of seeking to maximize the potential energy and is robust to local ground surface feature. Biomechanics literature indicates a similar strategy in play during human balance maintenance.