Bio-inspired control concepts for elastic rotatory joint drives

Annunziata S. Bio-inspired control concepts for elastic rotatory joint drives. Bielefeld: Universität Bielefeld; 2014.Recent research in robotics focuses the attention on the control of compliant actuators to improve safety and to make the interaction with humans more natural. Lightweight construction, real elasticity directly integrated into the joint and control of joint compliance seem to play the most important role for improving safety in human-machine interaction. Humans are intrinsically elastic and the Central Nervous System (CNS) takes advantage of the nonlinear muscle properties to modulate joint stiffness through co-contraction of antagonistic muscles. If alterable compliance in robotic systems is desirable, its introduction can be achieved in two fundamentally different ways. The first way is a technical approach based on the idea of impedance control as formulated by Hogan (1985). The second approach is bioinspired and introduces physiological control mechanisms, muscle models and virtual antagonistic actuation into the control system of a robotics joint drive. Recently, biological models for the control of muscles in vertebrates have been developed (Franklin et al., 2008; Yang et al., 2011). Still, the question remains, how a control algorithm, acting on two or even more muscles, can be implemented in a technical joint. With the objective to implement bio-inspired control strategies on a robotic joint drive, in this thesis, musculoskeletal models, biological parameters and bio-inspired control laws are analyzed and tested. A simplified model of the human elbow joint is used to analyze muscle-like actuation and stiffness properties at the joint. Based on recent results related to how the CNS controls antagonistic muscles, a biological control pattern based on reciprocal activation and co-activation is tested for the control of torque and stiffness at the joint. However, a closer analysis of the musculoskeletal parameters reveals that, despite antagonistic co-activation, domains in the joint range of motion might occur for which stiffness variation is limited (low stiffness variability) or even impossible (stiffness nodes). The first part of this thesis presents novel strategies for simultaneous control of torque and stiffness in a hinge joint actuated by two antagonistic muscle pairs. One strategy handles stiffness nodes by shifting them away from the current joint position and thus regaining stiffness controllability. To prevent domains of low stiffness variation, an optimal biomechanical setup is sought and finally defined which allows for a maximal stiffness variation across a wide angular joint range. Based on this optimal setup, four additional control approaches are designed and tested in simulation which deliver stiffnesses and torques comparable to those obtained in the optimal case. The control approaches combine biologically justified aspects, like reciprocal activation and co-activation, with novel ideas like inverse dynamics model and activation overflow. The second part of the thesis focuses on the design, test and validation of a bio-inspired position and stiffness control strategy for a lightweight, intrinsically elastic, robotics joint drive. Reciprocal activation and co-activation are used here as a starting point to concurrently control stiffness and position (instead of torque). A stability analysis, performed on the human elbow joint model, confirms that the co-activation level (and, as a consequence, the stiffness level) affects the reaction of the joint to external perturbations in terms of oscillations and settling time. To account for the stability aspects and implement further mechanisms found in the CNS of vertebrates, models of the muscle spindles, Golgi tendon organs, alpha-motor neurons and Renshaw cells, are added to the control algorithm. Nevertheless, while in many biological systems, antagonistic muscles generate the movement of the joint, in simple robotic systems, the movement is generated by only one actuator. Therefore, in order to transmit the desired bio-inspired movement to the technical elbow, the sum of all muscle-torques acting on the joint (i.e. the net-torque at the joint), has to be transmitted to the lightweight, inherently elastic, joint drive and controlled. A speed-torque control cascade is designed, implemented and tested on the robotics joint drive. The impedance range of the human elbow joint is evaluated in simulation and compared to the range obtained when the technical joint drive is acting instead of its biological counterpart. The bio-inspired controlled joint drive is able to reach the desired position and modulate joint compliance according to the disturbance like humans do, both in static cases and during movements, while keeping stability

Development in a biologically inspired spinal neural network for movement control

In two phases, we develop neural network models of spinal circuitry which self-organises into networks with opponent channels for the control of an antagonistic muscle pair. The self-organisation is enabled by spontaneous activity present in the spinal cord. We show that after the process of self-organisation, the networks have developed the possibility to independently control the length and tension of the innerated muscles. This allows the specification of joint angle independent from the specification of joint stiffness. The first network comprises only motorneurons and inhibitory interneurons through which the two channels interact. The inhibitory interneurons prevent saturation of the motorneuron pools, which is a necessary condition for independent control. In the second network, however, the neurons in the motorneuron pools obey the size-principle, which is a threat to the desired invariance of joint angle for varying joint stiffness, because of the different amplification of inputs in the case these inputs are not equal. To restore the desired invariance the second network ha.s been expanded with Renshaw cells. The manner in which they are included in the circuitry corrects the problem caused by the addition of the size-principle. The results obtained from the two models compare favourably with the FLETE-model for spinal circuitry (Bullock & Grossberg, 1991; Bullock et al., HJ93; Bullock & Contreras-Vidal, 1993) which has been successful in explaining several phenomena related to motor control.Fulbright Scholarship; Office of Naval Research (N00014-92-J-1309, N00014-95-1-0409

Towards an Autonomous Walking Robot for Planetary Surfaces

In this paper, recent progress in the development of the DLR Crawler - a six-legged, actively compliant walking robot prototype - is presented. The robot implements a walking layer with a simple tripod and a more complex biologically inspired gait. Using a variety of proprioceptive sensors, different reflexes for reactively crossing obstacles within the walking height are realised. On top of the walking layer, a navigation layer provides the ability to autonomously navigate to a predefined goal point in unknown rough terrain using a stereo camera. A model of the environment is created, the terrain traversability is estimated and an optimal path is planned. The difficulty of the path can be influenced by behavioral parameters. Motion commands are sent to the walking layer and the gait pattern is switched according to the estimated terrain difficulty. The interaction between walking layer and navigation layer was tested in different experimental setups

A variable stiffness soft gripper using granular jamming and biologically inspired pneumatic muscles

As the domains in which robots operate change the objects a robot may be required to grasp and manipulate are likely to vary significantly and often. Furthermore there is increasing likelihood that in the future robots will work collaboratively alongside people. There has therefore been interest in the development of biologically inspired robot designs which take inspiration from nature. This paper presents the design and testing of a variable stiffness, three fingered soft gripper which uses pneumatic muscles to actuate the fingers and granular jamming to vary their stiffness. This gripper is able to adjust its stiffness depending upon how fragile/deformable the object being grasped is. It is also lightweight and low inertia making it better suited to operation near people. Each finger is formed from a cylindrical rubber bladder filled with a granular material. It is shown how decreasing the pressure inside the finger increases the jamming effect and raises finger stiffness. The paper shows experimentally how the finger stiffness can be increased from 21 to 71 N/m. The paper also describes the kinematics of the fingers and demonstrates how they can be position-controlled at a range of different stiffness values