Bio-mimetic Adaptive Force/Position Control Using Fractal Impedance

The ability of animals to interact with complex dynamics is unmatched in robots. Especially important to the interaction performances is the online adaptation of body dynamics, which can be modeled as an impedance behaviour. However, the variable impedance controller still possesses a challenge in the current control frameworks due to the difficulties of retaining stability when adapting the controller gains. The fractal impedance controller has been recently proposed to solve this issue. However, it still has limitations such as sudden jumps in force when it starts to converge to the desired position and the lack of a force feedback loop. In this manuscript, two improvements are made to the control framework to solve these limitations. The force discontinuity has been addressed introducing a modulation of the impedance via a virtual antagonist that modulates the output force. The force tracking has been modeled after the parallel force/position controller architecture. In contrast to traditional methods, the fractal impedance controller enables the implementation of a search algorithm on the force feedback to adapt its behaviour on the external environment instead of on relying on \textit{a priori} knowledge of the external dynamics. Preliminary simulation results presented in this paper show the feasibility of the proposed approach, and it allows to evaluate the trade-off that needs to be made when relying on the proposed controller for interaction. In conclusion, the proposed method mimics the behaviour of an agonist/antagonist system adapting to unknown external dynamics, and it may find application in computational neuroscience, haptics, and interaction control.Comment: \c{opyright} 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Safe and Compliant Control of Redundant Robots Using Superimposition of Passive Task-Space Controllers

Safe and compliant control of dynamic systems in interaction with the environment, e.g., in shared workspaces, continues to represent a major challenge. Mismatches in the dynamic model of the robots, numerical singularities, and the intrinsic environmental unpredictability are all contributing factors. Online optimization of impedance controllers has recently shown great promise in addressing this challenge, however, their performance is not sufficiently robust to be deployed in challenging environments. This work proposes a compliant control method for redundant manipulators based on a superimposition of multiple passive task-space controllers in a hierarchy. Our control framework of passive controllers is inherently stable, numerically well-conditioned (as no matrix inversions are required), and computationally inexpensive (as no optimization is used). We leverage and introduce a novel stiffness profile for a recently proposed passive controller with smooth transitions between the divergence and convergence phases making it particularly suitable when multiple passive controllers are combined through superimposition. Our experimental results demonstrate that the proposed method achieves sub-centimeter tracking performance during demanding dynamic tasks with fast-changing references, while remaining safe to interact with and robust to singularities. he proposed framework achieves such results without knowledge of the robot dynamics and thanks to its passivity is intrinsically stable. The data further show that the robot can fully take advantage of the redundancy to maintain the primary task accuracy while compensating for unknown environmental interactions, which is not possible from current frameworks that require accurate contact information

A Null-space based Approach for a Safe and Effective Human-Robot Collaboration

During physical human robot collaboration, it is important to be able to implement a time-varying interactive behaviour while ensuring robust stability. Admittance control and passivity theory can be exploited for achieving these objectives. Nevertheless, when the admittance dynamics is time-varying, it can happen that, for ensuring a passive and stable behaviour, some spurious dissipative effects have to be introduced in the admittance dynamics. These effects are perceived by the user and degrade the collaborative performance. In this paper we exploit the task redundancy of the manipulator in order to harvest energy in the null space and to avoid spurious dynamics on the admittance. The proposed architecture is validated by simulations and by experiments onto a collaborative robot

Fractal Impedance for Passive Controllers

There is increasing interest in control frameworks capable of moving robots from industrial cages to unstructured environments and coexisting with humans. Despite significant improvement in some specific applications (e.g., medical robotics), there is still the need for a general control framework that improves interaction robustness and motion dynamics. Passive controllers show promising results in this direction; however, they often rely on virtual energy tanks that can guarantee passivity as long as they do not run out of energy. In this paper, a fractal attractor is proposed to implement a variable impedance controller that can retain passivity without relying on energy tanks. The controller generates a fractal attractor around the desired state using an asymptotic stable potential field, making the controller robust to discretization and numerical integration errors. The results prove that it can accurately track both trajectories and end-effector forces during interaction. Therefore, these properties make the controller ideal for applications requiring robust dynamic interaction at the end-effector.Comment: Video Available at https://youtu.be/S06_hqn3Nv

Whole-Body Teleoperation and Shared Control of Redundant Robots with Applications to Aerial Manipulation

This paper introduces a passivity-based control framework for multi-task time-delayed bilateral teleoperation and shared control of kinematically-redundant robots. The proposed method can be seen as extension of state-of-the art hierarchical whole-body control as it allows for some of the tasks to be commanded by a remotely-located human operator through a haptic device while the others are autonomously performed. The operator is able to switch among tasks at any time without compromising the stability of the system. To enforce the passivity of the communication channel as well as to dissipate the energy generated by the null-space projectors used to enforce the hierarchy among the tasks, the Time-Domain Passivity Approach (TDPA) is applied. The efficacy of the approach is demonstrated through its application to the DLR Suspended Aerial Manipulator (SAM) in a real telemanipulation scenario with variable time delay, jitter, and package loss

Passivation of Projection-Based Null Space Compliance Control Via Energy Tanks

A manipulator with kinematic redundancy w.r.t. a main task enables to perform an additional, subordinate task in its null space. The classical hierarchy-based approach is to apply dynamically consistent null space projections such that this lower-priority task does not disturb the main task. The major problem is that the control task hierarchy is established at the expense of the passivity of the system, which causes problems in terms of stability, robustness, and safety. Here, we extend this classical approach and passivate the closed-loop system by means of an energy tank, which is filled by the dissipated power of the active damping on both hierarchy levels. We validate the method in simulations and experiments on a torque-controlled manipulator. The concept is predestined for physical humanrobot interaction and safety-relevant applications, where passivity must be guaranteed