Impedence Control for Variable Stiffness Mechanisms with Nonlinear Joint Coupling

The current discussion on physical human robot interaction and the related safety aspects, but also the interest of neuro-scientists to validate their hypotheses on human motor skills with bio-mimetic robots, led to a recent revival of tendondriven robots. In this paper, the modeling of tendon-driven elastic systems with nonlinear couplings is recapitulated. A control law is developed that takes the desired joint position and stiffness as input. Therefore, desired motor positions are determined that are commanded to an impedance controller. We give a physical interpretation of the controller. More importantly, a static decoupling of the joint motion and the stiffness variation is given. The combination of active (controller) and passive (mechanical) stiffness is investigated. The controller stiffness is designed according to the desired overall stiffness. A damping design of the impedance controller is included in these considerations. The controller performance is evaluated in simulation

The intelligent design of evolution

Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With Rollin’ Justin a mobile robotic system and research platform is presented that allows the implementation and demonstration of sophisticated control algorithms and dexterous manipulation. Important problems of service robotics such as mobile manipulation and strategies for using the increased workspace and redundancy in manipulation task can be studied in detail. This paper gives an overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system Justin into Rollin’ Justin, a fully self-sustaining mobile research platform

Kinematically Optimal Catching a Flying Ball with a Hand-Arm-System

A robotic ball-catching system built from a multi- purpose 7-DOF lightweight arm (DLR-LWR-III) and a 12 DOF four-fingered hand (DLR-Hand-II) is presented. Other than in previous work a mechatronically complex dexterous hand is used for grasping the ball and the decision of where, when and how to catch the ball, while obeying joint, speed and work cell limits, is formulated as an unified nonlinear optimization problem with nonlinear constraints. Three different objective functions are implemented, leading to significantly different robot movements. The high computational demands of an online realtime optimization are met by parallel computation on distributed computing resources (a cluster with 32 CPU cores). The system achieves a catch rate of > 80% and is regularly shown as a live demo at our institute

Experimental Study on Dynamic Reactionless Motions with DLR’s Humanoid Robot Justin

The capabilities of DLR’s multi-DOF humanoid robot Justin are extended with the help of a dynamic torque control component for base reaction minimization. Since the mobile base of the robot comprises springs, reactions induced by arm/torso motions lead to vibrations and deteriorate the performance. The control component is derived from the equation of motion of the robot, represented as an underactuated system, and partitioned into a “driven” subsystem (one of the arms), and a “compensating” subsystem (the other arm, with or w/o torso contribution). The control component is then embedded into the existing sophisticated controller structure of Justin, as a feedforward component, with additional control signals from an augmented PD feedback controller. It was possible to obtain satisfactory performance with a very “soft” compensatory subsystem. The experimental results confirmed the potential of this model-based approach for use in a complex multi-DOF system. As far as we know, this is the first time that a dynamic-coupling compensating controller is applied to a real system of such complexity, utilizing thereby a torque control interface

Dynamic Whole-Body Mobile Manipulation with a Torque Controlled Humanoid Robot via Impedance Control Laws

Service robotics is expected to be established in human households and environments within the next decades. Therefore, dexterous and flexible behavior of these systems as well as guaranteeing safe interaction are crucial for that progress. We address these issues in terms of control strategies for the whole body of DLR's humanoid Justin. Via impedance control laws, we enable the robot to realize main tasks compliantly while, at the same time, taking care of aspects like physical limitations and collision avoidance with its own structure and the environment autonomously. The controller provides a natural redundancy resolution between the arms, the torso and the wheeled platform. A low-dimensional task space interface is proposed that can be used by planning tools. Thereby, planning time can be saved significantly. Experimental results on DLR's Justin are presented to validate our approach

Analysis and Experimental Evaluation of the Intrinsically Passive Controller (IPC) for Multifingered Hands

The object level control of a dexterous robot hand provides an intuitive high-level interface to solve fine manipulation tasks. In the past, many algorithms were proposed based on a weighted pseudoinverse of the grasp map. In a different approach Stramigioli introduces a virtual object - called “Intrinsically Passive Controller (IPC)”. This controller distributes the generalized object forces using coupling springs whose weighting have an intuitive physical meaning. Even though this controller has been known for several years we will present the first experimental results for a four-fingered hand. Furthermore, the term virtual grasp map is introduced and a method to parameterize the stiffness parameters in order to obtain an effective object level stiffness and a damping design is proposed. An implementation of the IPC is tested on the DLR Hand II and its performance is analyzed by manipulating soft and stiff objects

Singularity Avoidance for Nonholonomic, Omnidirectional Wheeled Mobile Platforms with Variable Footprint

One characteristic attribute of mobile platforms equipped with a set of independent steering wheels is their omnidirectionality and the ability to realize complex translational and rotational trajectories. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. Since the orientations of the wheels must align to the Instantaneous Center of Rotation (ICR), the current location and velocity of this specific point is essential for describing the state of the platform. However, singular configurations of the controlled system exist depending on the ICR, leading to unfeasible control inputs, i.e., infinite steering rates. Within this work we address and analyze this problem in general. Furthermore, we propose a solution for mobile platforms with variable footprint. An existing controller based on dynamic feedback linearization is augmented by a new potential field-based algorithm for singularity avoidance which uses the tunable leg lengths as an additional control input to minimize deviations from the nominal motion trajectory. Simulations and experimental results on the mobile platform of DLR's humanoid manipulator Justin support our approach

Feedback linearization and simultaneous stiffness-position control of robots with antagonistic actuated joints.

In this paper, the dynamic model of a robot with antagonistic actuated joints is presented, and the problem of full linearization via static state feedback is analyzed. The use of transmission elements with nonlinear relation between the displacement and the actuated force allows to control both the position and the stiffness of each joint. The main advantage of this actuation modality is that the achieved stiffness becomes same mechanical characteristic of the system and it is not the result of an immediate control action as in the classical impedance control scheme. Different examples of implementation of this kind of devices are known in literature, even if limited to one single joint and the application of antagonistic actuated kinematic chains in the field of robotic hand design is under investigation. After a brief review of the dependence of the properties of antagonistic actuation on the transmission elements characteristics, a scheme for simultaneous stiffness-position control of the linearized system is presented. Finally, simulation results of a two-link antagonistic actuated arm are reported and discussed