Exploiting adaptable passive behaviour to influence natural dynamics applied to legged robots

Verrelst, Björn; Ham, Ronald Van; Vanderborght, Bram; Vermeulen, Jimmy; Lefeber, Dirk; Daerden, F.

doi:10.1017/s0263574704000669

Cited by 21 publications

(14 citation statements)

References 21 publications

(22 reference statements)

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“…The optimisation of the passive system properties has also been discussed under more dynamic conditions. In this context, [22,23], demonstrated that tracking a small amplitude oscillatory motion of a pendulum can be made efficient by matching the (constant) stiffness of the actuators with the natural stiffness of the reference trajectory. With a similar objective in [20], the authors combined trajectory tracking with adaptation of the constant joint stiffness to its optimal value.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Variable Stiffness in Explosive Movement Tasks

Braun¹,

Howard²,

Vijayakumar³

2011

Robotics: Science and Systems VII

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Abstract-It is widely recognised that compliant actuation is advantageous to robot control once high-performance, explosive tasks, such as throwing, hitting or jumping are considered. However, the benefit of intrinsic compliance comes with high control complexity. Specifically, coordinating the motion of the system through a compliant actuator and finding a task-specific impedance profile that leads to better performance is non-trivial. Here, we utilise optimal control to devise time-varying torque and stiffness profiles for highly dynamic movements in compliantly actuated robots. The proposed methodology is applied to a ballthrowing task where we demonstrate that: (i) the method is able to tailor impedance strategies to specific task objectives and system dynamics, (ii) the ability to vary stiffness leads to better performance in this class of movements, (iii) in systems with variable physical compliance, our methodology is able to exploit the energy storage capabilities of the actuators. We illustrate these in several numerical simulations, and in hardware experiments on a device with variable physical stiffness.

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Section: Introductionmentioning

confidence: 99%

Exploiting Variable Stiffness in Explosive Movement Tasks

Braun¹,

Howard²,

Vijayakumar³

2011

Robotics: Science and Systems VII

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“…The mean value p m will determine the joint stiffness and will be controlled in order to influence the natural dynamics of the system [19]. Feeding back the joint angle b and using expression (2), Dp can be determined by:…”

Section: Robot Controlmentioning

confidence: 99%

Treadmill walking of the pneumatic biped Lucy: Walking at different speeds and step-lengths

et al. 2008

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Actuators with adaptable compliance are gaining interest in the field of legged robotics due to their capability to store motion energy and to exploit the natural dynamics of the system to reduce energy consumption while walking and running. To perform research on compliant actuators we have built the planar biped Lucy. The robot has six actuated joints, the ankle, knee and hip of both legs with each joint powered by two pleated pneumatic artificial muscles in an antagonistic setup. This makes it possible to control both the torque and the stiffness of the joint. Such compliant actuators are used in passive walkers to overcome friction when walking over level ground and to improve stability. Typically, this kind of robots is only designed to walk with a constant walking speed and step-length, determined by the mechanical design of the mechanism and the properties of the ground. In this paper, we show that by an appropriate control, the robot Lucy is able to walk at different speeds and step-lengths and that adding and releasing weights does not affect the stability of the robot. To perform these experiments, an automated treadmill was built Keywords: bipedal walking robot, pneumatic artificial muscle 1. Introduction. Bipedal robots are gaining interest because of their potential for higher mobility than that of wheeled vehicles. Although for an outsider in the field walking is very obvious, the fastest robot at the moment is Asimo with a top running speed of 6 km/h. A study on humanoid robots performed by FZI [1] forecasts that it will take about 10-20 years before bipeds can even with humans. The best-known humanoid robots are Asimo [2], Qrio [3], and HRP-2 [4], all actuated by classical electric drives. Nowadays, research is performed to develop soft or compliant actuators and implement them in bipeds. A study of the control system of robots in which soft actuators were used can be found in [5] for a sagittal hopping robot, [6, 7] for a 3D hopping robot, and [8] for a walking biped. Other publications [9][10][11][12] can be noted, in which the problems of control of similar systems are considered. Main reason is to reduce the energy consumption of those robots by exploiting the natural dynamics of the system. The "Passive walkers" do not even need actuation at all to walk down a sloped surface or only use a limited amount of actuation when walking over level ground just enough to overcome friction. Examples are the Cornell biped, the Delft biped Denise, and MIT robot Toddler [13]. Unfortunately, they are of little practical use. They have difficulties to start, cannot change their speed, and cannot stop, contrary to a completely actuated robot. Adding control while exploiting the natural dynamics of the system will be probably the optimal. The way we want to find this optimal is by using actuators with controllable compliance just like humans do.As compliant or soft actuator we propose the Pleated Pneumatic Artificial Muscle for which an elaborate control has been developed. The control of such actuator is new....

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“…Doing so includes the muscle actuator characteristics, which allows the limitations in the motion of the pendulum to be studied. Detailed information on the simulation model can be found in (Verrelst, 2005a) for a one degree of freedom setup and in (Verrelst, 2005b) for the complete biped, elaborated on in section 5. To test the robustness, model parameter uncertainties are introduced in the simulation model, e.g.…”

Section: Simulatormentioning

confidence: 99%