Vittorio Lippi

Good Posture, Good Balance: Comparison of Bioinspired and Model-Based Approaches for Posture Control of Humanoid Robots

This article provides a theoretical and thorough experimental comparison of two distinct posture control approaches: (1) a fully model-based control approach and (2) a biologically inspired approach derived from human observations. While the robotic approach can easily be applied to balancing in three-dimensional (3-D) and multicontact (MC) situations, the biologically inspired balancer currently only works in two-dimensional situations 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 (TORO). This article concludes with some suggestions for the improvement of model-based balancing approaches in robotics.

Benchmarking Human-Like Posture and Locomotion of Humanoid Robots: A Preliminary Scheme

The difficulty in defining standard benchmarks for human likeness is a well-known problem in bipedal robotics. This paper proposes the conceptual design of a novel benchmarking scheme for bipedal robots based on existing criteria and benchmarks related to the sensorimotor mechanisms involved in human walking and posture. The proposed scheme aims to be sufficiently generic to permit its application to a wide range of bipedal platforms, and sufficiently specific to rigorously test the sensorimotor skills found in humans.

Human-Derived Disturbance Estimation and Compensation (DEC) Method Lends Itself to a Modular Sensorimotor Control in a Humanoid Robot

The high complexity of the human posture and movement control system represents challenges for diagnosis, therapy, and rehabilitation of neurological patients. We envisage that engineering-inspired, model-based approaches will help to deal with the high complexity of the human posture control system. Since the methods of system identification and parameter estimation are limited to systems with only a few DoF, our laboratory proposes a heuristic approach that step-by-step increases complexity when creating a hypothetical human-derived control systems in humanoid robots. This system is then compared with the human control in the same test bed, a posture control laboratory. The human-derived control builds upon the identified disturbance estimation and compensation (DEC) mechanism, whose main principle is to support execution of commanded poses or movements by compensating for external or self-produced disturbances such as gravity effects. In previous robotic implementation, up to 3 interconnected DEC control modules were used in modular control architectures separately for the sagittal plane or the frontal body plane and successfully passed balancing and movement tests. In this study we hypothesized that conflict-free movement coordination between the robots sagittal and frontal body planes emerges simply from the physical embodiment, not necessarily requiring a full body control. Experiments were performed in the 14 DoF robot Lucy Posturob (i) demonstrating that the mechanical coupling from the robots body suffices to coordinate the controls in the two planes when the robot produces movements and balancing responses in the intermediate plane, (ii) providing quantitative characterization of the interaction dynamics between body planes including frequency response functions (FRFs), as they are used in human postural control analysis, and (iii) witnessing postural and control stability when all DoFs are challenged together with the emergence of inter-segmental coordination in squatting movements. These findings represent an important step toward controlling in the robot in future more complex sensorimotor functions such as walking.

Human-Inspired Eigenmovement Concept Provides Coupling-Free Sensorimotor Control in Humanoid Robot

Control of a multi-body system in both robots and humans may face the problem of destabilizing dynamic coupling effects arising between linked body segments. The state of the art solutions in robotics are full state feedback controllers. For human hip-ankle coordination, a more parsimonious and theoretically stable alternative to the robotics solution has been suggested in terms of the Eigenmovement (EM) control. Eigenmovements are kinematic synergies designed to describe the multi DoF system, and its control, with a set of independent, and hence coupling-free, scalar equations. This paper investigates whether the EM alternative shows “real-world robustness” against noisy and inaccurate sensors, mechanical non-linearities such as dead zones, and human-like feedback time delays when controlling hip-ankle movements of a balancing humanoid robot. The EM concept and the EM controller are introduced, the robots dynamics are identified using a biomechanical approach, and robot tests are performed in a human posture control laboratory. The tests show that the EM controller provides stable control of the robot with proactive (“voluntary”) movements and reactive balancing of stance during support surface tilts and translations. Although a preliminary robot-human comparison reveals similarities and differences, we conclude (i) the Eigenmovement concept is a valid candidate when different concepts of human sensorimotor control are considered, and (ii) that human-inspired robot experiments may help to decide in future the choice among the candidates and to improve the design of humanoid robots and robotic rehabilitation devices.

Posture Control—Human-Inspired Approaches for Humanoid Robot Benchmarking: Conceptualizing Tests, Protocols and Analyses

Posture control is indispensable for both humans and humanoid robots, which becomes especially evident when performing sensorimotor tasks such as moving on compliant terrain or interacting with the environment. Posture control is therefore targeted in recent proposals of robot benchmarking in order to advance their development. This Methods article suggests corresponding robot tests of standing balance, drawing inspirations from the human sensorimotor system and presenting examples from robot experiments. To account for a considerable technical and algorithmic diversity among robots, we focus in our tests on basic posture control mechanisms, which provide humans with an impressive postural versatility and robustness. Specifically, we focus on the mechanically challenging balancing of the whole body above the feet in the sagittal plane around the ankle joints in concert with the upper body balancing around the hip joints. The suggested tests target three key issues of human balancing, which appear equally relevant for humanoid bipeds: (1) four basic physical disturbances (support surface (SS) tilt and translation, field and contact forces) may affect the balancing in any given degree of freedom (DoF). Targeting these disturbances allows us to abstract from the manifold of possible behavioral tasks. (2) Posture control interacts in a conflict-free way with the control of voluntary movements for undisturbed movement execution, both with “reactive” balancing of external disturbances and “proactive” balancing of self-produced disturbances from the voluntary movements. Our proposals therefore target both types of disturbances and their superposition. (3) Relevant for both versatility and robustness of the control, linkages between the posture control mechanisms across DoFs provide their functional cooperation and coordination at will and on functional demands. The suggested tests therefore include ankle-hip coordination. Suggested benchmarking criteria build on the evoked sway magnitude, normalized to robot weight and Center of mass (COM) height, in relation to reference ranges that remain to be established. The references may include human likeness features. The proposed benchmarking concept may in principle also be applied to wearable robots, where a human user may command movements, but may not be aware of the additionally required postural control, which then needs to be implemented into the robot.

Human-Inspired Humanoid Balancing and Posture Control in Frontal Plane

Human balancing can be modeled for the sagittal and frontal planes using double inverted pendulum (DIP) biomechanics representations. The DIP approach has also been used in the DEC (disturbances estimation and compensation) model for balance control of a humanoid robot in the sagittal plane. In this paper, it is implemented on a 14 degrees of freedom humanoid for the frontal plane. Positive results open the possibility to use the DEC concept for a bio-inspired modular control architecture for both the sagittal and the frontal planes.

Postural balance using a disturbance rejection method

In this paper the synthesis of balance control is presented. The postural equilibrium condition is introduced using a simplified model of a humanoid robot body. Next the problem of disturbances rejection control (DRC) using dedicated controller is discussed. The simulation experiments with the DRC are described, and the system behavior during different disturbances is summarized. The paper ends with concluding remarks. The concept of postural balancing control using especially synthesized DRC controller which incorporates the robot dynamics is the novel contribution of this work. The controller allows not only to hold the static posture but also to follow dynamically the sway of supporting surface by rejecting the influence of disturbances. The work is focusing on the real application. The postural stability was tested using the simulator of robot dynamics what made the final validation of the method before implementing it in the real robot.

Human-Like Sensor Fusion Implemented in the Posture Control of a Bipedal Robot

Posture control represents the basis for many human sensorimotor activities such as standing, walking or reaching. It involves inputs from joint angle, joint torque, vestibular and visual sensors as well as fusions of the sensor data. Roboticists may draw inspirations from the human posture control methods when building devices that interact with humans such as prostheses or exoskeletons. This study describes multisensory fusion mechanisms that were derived from human perception of ego-motion. They were implemented in a posture control model that describes human balancing of biped stance during external disturbances. The fusions are used for estimating the disturbances and the estimates, in turn, command joint servo controls to compensate them (disturbance estimation and compensation, DEC, concept). An emergent property of the network of sensory estimators is an automatic adaptation to changes in disturbance type and magnitude and in sensor availability. Previously, the model described human and robot balancing about the ankle joints in the sagittal plane. Here, the approach is extended to include the hip joints. The extended human-derived model is again re-embodied in a biped posture control robot constructed with human anthropometrics. The robot is tested in direct comparison with human subjects. Results on hip and ankle sway responses to support surface rotation are described. Basic resemblance of the results suggests that the robot’s DEC controls capture important aspects of the human balancing.