Elastic Structure Preserving Impedance (ESPi) Control for Compliantly Actuated Robots

We present a new approach for Cartesian impedance control of compliantly actuated robots with possibly nonlinear spring characteristics. It reveals a remarkable stiffness and damping range in the experimental evaluation. The most interesting contribution, is the way the desired closed-loop dynamics is designed. Our control concept allows to add a desired stiffness and damping directly on the end-effector, while leaving the system structure intact. The intrinsic inertial and elastic properties of the system are preserved. This is achieved by introducing new motor coordinates that reflect the desired spring and damper terms. Theoretically, by means of additional motor inertia shaping it is possible to make the end-effector interaction behavior with respect to external loads approach, arbitrarily close, the interaction behavior that is achievable by classical Cartesian impedance control on rigid robots. The physically motivated design approach allows for an intuitive understanding of the resulting closed-loop dynamics. We perform a passivity and stability analysis on the basis of al physically motivated storage and Lyapunov function

Vibration Damping for Highly Compliant Robots

In order to guarantee save interaction of robots with the environment and to ensure mechanical robustness, one of the key technical properties of robotic systems is physical compliance of the actuation systems. This is mostly achieved by a highly elastic element decoupling the link from the motor. The flexible elements cause a partially undesired vibration dynamics in the robotic structure when excited with harmonic torque on the link sides. The aim of this thesis is to analyze and to reduce oscillations through optimally chosen settings of the controller. To achieve that, we focus on two control approaches, namely Elastic Structure Preserving Impedance (ESpi) and Visco-Elastic Structure Preserving Impedance (VESpi) controller developed by Keppler et al. in [Kep+18a] and [Kep+18b]. To analyze the closed loop system, we focus on a non-tracking case, one joint and linear spring characteristic. As the aim is to absorb the introduced energy as efficiently as possible, we investigate the effect on certain tuning par meters. The physically motivated design approach of ESpi and VESpi controllers enables us to represent the closed-loop system as a nonconservative multispring-damper two-mass oscillator. Taking the concept of a tuned mass damper (TMD) into account, we extend the existing rule of how to choose the impedance of the absorber presented in for use in the VESpi and ESpi system. This is achieved in two steps: Firstly, we derive an analytical model of the closed-loop system and find parameters for the minimax amplitude in the frequency response. Secondly, we run a Monte Carlo simulation using a visco-elastic two-mass-system controlled by ESpi and VESpi. We want to obtain cost values for vibration and power efficiency that represent vibration efficiency and control effort. The results provide a guideline to determine the parameters for either minimum amplitude at link-side or best power efficiency. One of the most interesting contributions is that the VESpi controller - in contrast to ESpi - features optimal damping characteristic for all excitation frequencies given the optimal setting. On the other hand, the control approach ESpi cannot be used as a TMD due to the placement of the damper. Nevertheless, an optimal setting for a wide range of frequencies can be found

Tele Running - Energy Efficient Locomotion for Elastic Joint Robots by Imitation Learning

This thesis presents an imitation learning approach to energy-efficient trajectory generation for elastic, legged robots. The trajectories are generated by teleoperation with force feedback. The presented framework allows an operator to achieve locomotion on an one-leg hopper by controlling its foot tip. The force feedback is designed to assist the operator to find gaits which exploit the natural harmonics of the hopper and thus improve energy efficiency. The resulting trajectory is approximated, parameterized, and replayed on the robot. The operator achieves a cost of transport of 0.25 at 0.63 m/s, considering the mechanical energy. Black-box optimization is used to keep this value with varying hardware parameters, such as different foot-tip stiffness. A reinforcement learning algorithm stabilizes lateral movement by active balance in simulation. Learning on hardware shows an improvement in stability. The concept is extended to multi-legged robots by teleoperating the two feet of the biped DLR C-Runner in simulation. The force feedback assists the operator to find stable gaits where the center of mass does not leave the support polygon of the feet. On both systems, the presented teleoperation framework utilizes the human's capability of estimating the properties of non-linear dynamics by designing appropriate haptic feedback

Analysis of Actuator Control Strategies for Excitation of Intrinsic Modes in Compliant Robots with Series Elastic Actuators

In biology, body dynamics and elasticity in periodic motions most likely con- tribute to efficiency, i.e., in mammalian locomotion. Likewise, elastic elements can be added to robotic systems in an attempt to mimic this biological concept. Compliant robots are less likely to get damaged after severe impacts and their mechanical energy storage via springs could be exploited for fast and explosive movements. In this thesis, we explore the question whether resonance excitation that solely considers link-side dynamics or also takes into account the motor inertia, can lead to an increase in performance in Series Elastic Actuator (SEA) driven robotic systems. We propose three different control approaches and compare them to compliant state-of-the-art control as baseline evaluation in simulation and hardware experiments. Moreover, we extend the investigation of motor-side-excitation with the aid of methods such as inertia shaping and simulative system variation. Experiment results regarding a pick-and-place task with fixed amplitude reveal that in the investigated test setup, it might not be beneficial to make dedicated use of the motor inertia. Instead, an approach that exclusively excites link-side dynamics appears, for this particular task and setup, to be advantageous. However, generally, also making use of the motor dynamics bears potential for specific investigations as it appears more flexible and the control behavior can be easily adapted. Thus, the presented thesis provides first fundamental insights about novel control strategies and lies the foundation for further systematic research with different actuation types and varying task goals

Robust Stabilization of Elastic Joint Robots by ESP and PID Control: Theory and Experiments

This work addresses the problem of global set-point control of elastic joint robots by combining elastic structure preserving (ESP) control with non-collocated integral action. Despite the popularity and extensive research on PID control for rigid joint robots, such schemes largely evaded adoption to elastic joint robots. This is mainly due to the underactuation inherent to these systems, which impedes the direct implementation of PID schemes with non-collocated (link position) feedback. We remedy this issue by using the recently developed concept of “quasi-full actuation,” to achieve a link-side PID control structure with “delayed” integral action. The design follows the structure preserving design philosophy of ESP control and ensures global asymptotic stability and local passivity of the closed loop. A key feature of the proposed controller is the switching logic for the integral action that enables the combination of excellent positioning accuracy in free motion with compliant manipulation in contact with the environment. Its performance is evaluated on an elastic joint testbed and a compliant robot arm. The results demonstrate that elastic robots may achieve positioning accuracy comparable to rigid joint robots

Simultaneous Motion Tracking and Joint Stiffness Control of Bidirectional Antagonistic Variable-Stiffness Actuators

Since safe human-robot interaction is naturally linked to compliance in these robots, this requirement presents a challenge for the positioning accuracy. The class of variable- stiffness robots features intrinsically soft contact behavior where the physical stiffness can even be altered during operation. Here we present a control scheme for bidirectional, antagonistic variable-stiffness actuators that achieve high-precision link-side trajectory tracking while simultaneously ensuring compliance during physical contact. Furthermore, the approach enables to regulate the pretension in the antagonism. The theoretical claims are confirmed by formal analyses of passivity during physical interaction and the proof of uniform asymptotic stability of the desired link-side trajectories. Experiments on the forearm joint of the DLR robot David verify the proposed approach

Safety Awareness for Rigid and Elastic Joint Robots: An Impact Dynamics and Control Framework

This thesis aims at making robots with rigid and elastic joints aware of human collision safety. A framework is proposed that captures human injury occurrence and robot inherent safety properties in a unified manner. It allows to quantitatively compare and optimize the safety characteristics of different robot designs and is applied to stationary and mobile manipulators. On the same basis, novel motion control schemes are developed and experimentally validated