Efficient computation of inverse dynamics and feedback linearization for VSA-based robots

We develop a recursive numerical algorithm to compute the inverse dynamics of robot manipulators with an arbitrary number of joints, driven by variable stiffness actuation (VSA) of the antagonistic type. The algorithm is based on Newton-Euler dynamic equations, generalized up to the fourth differential order to account for the compliant transmissions, combined with the decentralized nonlinear dynamics of the variable stiffness actuators at each joint. A variant of the algorithm can be used also for implementing a feedback linearization control law for the accurate tracking of desired link and stiffness trajectories. As in its simpler versions, the algorithm does not require dynamicmodeling in symbolic form, does not use numerical approximations, grows linearly in complexity with the number of joints, and is suitable for online feedforward and real-time feedback control. A Matlab/C code is made available

Numerical solutions for design and dynamic control of compliant robots

This work is focused on the development of numerical methods for the design and control of robots, with particular emphasis on joint elasticity. First, a general methodology is presented that is able to solve the problem of computing the inverse dynamics of a serial robot manipulator with an arbitrarily large number of elastic joints in a recursive numerical way. The solution algorithm is a generalized version of the standard Newton-Euler approach. The algorithm is presented with numerous extensions and variants, including the extension to variable-stiffness technologies and control applications. Then, an optimization framework is introduced for the design and analysis of biped walkers characterized by elastic joints, with comparative results demonstrating the scope of application of joint compliance in bipedal walking

Motion Planning for Multi-Contact Visual Servoing on Humanoid Robots

International audienceThis paper describes the implementation of a canonical motion generation pipeline guided by vision for a TALOS humanoid robot. The proposed system is using a mul-ticontact planner, a Differential Dynamic Programming (DDP) algorithm, and a stabilizer. The multicontact planner provides a set of contacts and dynamically consistent trajectories for the Center-Of-Mass (CoM) and the Center-Of-Pressure (CoP). It provides a structure to initialize a DDP algorithm which, in turn, provides a dynamically consistent trajectory for all the joints as it integrates all the dynamics of the robot, together with rigid contact models and the visual task. Tested on Gazebo the resulting trajectory had to be stabilized with a state-of-the-art algorithm to be successful. In addition to testing motion generated from high specifications to the stabilized motion in simulation, we express visual features at Whole Body Generator level which is a DDP formulated solver. It handles non-linearities as the ones introduced by the projections of visual features expressed and minimized in the image plan of the camera

Liver Trauma

The liver is the most frequently injured abdominal organ. Abdominal injuries occur in 31% of patients of polytrauma with 13 and 16% spleen and liver injuries respectively, and pelvic injuries in 28% of cases, making differential diagnosis between pelvic or intractable abdominal injury difficult.[1] Liver trauma is the most common cause of death after abdominal injury. The most common cause of liver injury is blunt abdominal trauma. Identification of serious intra-abdominal trauma is often challenging; many injuries may not manifest during the initial assessment and treatment period. Liver frequently injured following abdominal trauma and associated injuries contribute significantly to mortality and morbidity, and may mask the liver injury and causes delay in diagnosis. Management of hepatic injuries has evolved over the past 30 years. Prior to that time, a diagnostic peritoneal lavage (DPL) positive for blood, was an indication for exploratory celiotomy because of concern about ongoing hemorrhage and/or missed intra-abdominal injuries needing repair. The recognition that between 50 and 80 per cent of liver injuries stop bleeding spontaneously, coupled with better imaging of the injured liver by computed tomography (CT) and efficient ICU management, has led progressively to the acceptance of nonoperative management (NOM) with a resultant decrease in mortality rates

Combining real and virtual sensors for measuring interaction forces and moments acting on a robot

We address the problem of estimating an external wrench acting along the structure of a robot manipulator, together with the contact position where the external force is being applied. For this, we consider the combined use of a force/torque sensor mounted at the robot base and of a model-based virtual sensor. The virtual sensor is provided by the residual vector commonly used for collision detection and isolation in human-robot interaction. Integrating the two types of measurement tools provides an efficient way to estimate all unknown quantities, using also the recursive Newton- Euler algorithm for dynamic computations. Different operative conditions are considered, including the special cases of point- wise interaction (pure contact force), known contact location, and of a base sensor measuring only forces. We highlight also the conditions for a correct estimation to be fully virtual, i.e., without resorting to a force/torque sensor. Realistic simulations assess the estimation performance for a 7R robot in motion, subject to an unknown external force applied to an unknown location

A recursive Newton-Euler algorithm for robots with elastic joints and its application to control

We consider the problem of computing the inverse dynamics of a serial robot manipulator with N elastic joints in a recursive numerical way. The solution algorithm is a generalized version of the standard Newton-Euler approach, running still with linear complexity O(N) but requiring to set up recursions that involve higher order derivatives of motion and force variables. Mimicking the case of rigid robots, we use this algorithm and a numerical factorization of the link inertia matrix (which needs to be inverted in the elastic joint case) for implementing on-line a feedback linearization control law for trajectory tracking purposes. The complete method has a complexity that grows as O(N^3). The developed tools are generic, easy to use, and do not require symbolic Lagrangian modeling and customization, thus being of particular interest when the number N of elastic joints becomes large

Protocentric Aerial Manipulators: Flatness Proofs and Simulations

This document is a technical report that reports the results and proofs of the differential flatness of protocentric manipulators

Differential Flatness and Control of Protocentric Aerial Manipulators with Any Number of Arms and Mixed Rigid-/Elastic-Joints

International audienceIn this paper we introduce a particularly relevant class of aerial manipulators that we name protocentric. These robots are formed by an underactuated aerial vehicle, a planar-Vertical TakeOff and Landing (PVTOL), equipped with any number of different parallel manipulator arms with the only property that all the first joints are attached at the Center of Mass (CoM) of the PVTOL, while the center of actuation of the PVTOL can be anywhere. We prove that protocentric aerial manipulators (PAMs) are differentially flat systems regardless the number of joints of each arm and their kinematic and dynamic parameters. The set of flat outputs is constituted by the CoM of the PVTOL and the absolute orientation angles of all the links. The relative degree of each output is equal to four. More amazingly, we prove that PAMs are differentially flat even in the case that any number of the joints are elastic, no matter the internal distribution between elastic and rigid joints. The set of flat outputs is the same but in this case the total relative degree grows quadratically with the number of elastic joints. We validate the theory by simulating object grasping and transportation tasks with unknown mass and parameters and using a controller based on dynamic feedback linearization

Explicit Computations, Simulations and additional Results for the Dynamic Decentralized Control for Protocentric Aerial Manipulators

Technical Attachment to:”Dynamic Decentralized Control for Protocentric Aerial Manipulators” 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017This document is a technical attachment to ”Dynamic Decentralized Control for Protocentric Aerial Manipulators” for explicitcomputations of the nominal states and the inputs of a Pro-tocentric Aerial Manipulator (PAM) in 2D, using differentialflatness property. In ”Dynamic Decentralized Control for Protocentric Aerial Manipulators” these values are used to control aPAM in 3D. Furthermore, considering the aerial manipulatordesign used for the experiments in that paper, here we inves-tigate the case when the system is non-protocentric; i.e., themanipulating arm is not exactly attached to the CoM of theflying robot, P0 . We show the effect of the distance betweenthis attachment point and P0 on the performance tracking acomposite trajectory. Finally some additional plots related tothe experimental results are provided

Dynamic Decentralized Control for Protocentric Aerial Manipulators

We present a control methodology for underactuated aerial manipulators that is both easy to implement on real systems and able to achieve highly dynamic behaviours. The method is composed by two parts, a nominal input/state generator that takes into account the full-body nonlinear and coupled dynamics of the system, and a decentralized feedback controller acting on the actuated degrees of freedom that confers the needed robustness to the closed-loop system. We show how to apply the method to Protocentric Aerial Manipulators (PAM) by first using their differential flatness property on the vertical 2D plane in order to generate dynamical input/state trajectories, then statically extending the 2D structure to the 3D, and finally closing the loop with a decentralized controller having the dual task of both ensuring the preservation of the proper static 3D immersion and tracking the dynamic trajectory on the vertical plane. We demonstrate that the proposed controller is able to precisely track dynamic trajectories when implemented on a standard hardware composed by a quadrotor and a robotic arm with servo-controlled joints (even if no torque control is available). Comparative experiments clearly show the benefit of using the nominal input/state generator, and also the fact that the use of just static gravity compensation might surprisingly perform worse, in dynamic maneuvers, than the case of no compensation at all. We complement the experiments with additional realistic simulations testing the applicability of the proposed method to slightly non-protocentric aerial manipulators