Nathanaël Jarrassé

Connecting a Human Limb to an Exoskeleton

When developing robotic exoskeletons, the design of physical connections between the device and the human limb to which it is connected is a crucial problem. Indeed, using an embedment at each connection point leads to uncontrollable forces at the interaction port, induced by hyperstaticity. In practice, these forces may be large because in general the human limb kinematics and the exoskeleton kinematics differ. To cope with hyperstaticity, the literature suggests the addition of passive mechanisms inside the mechanism loops. However, empirical solutions that are proposed so far lack proper analysis and generality. In this paper, we study the general problem of connecting two similar kinematic chains through multiple passive mechanisms. We derive a constructive method that allows the determination of all the possible distributions of freed degrees of freedom across different fixation mechanisms. It also provides formal proofs of global isostaticity. Practical usefulness is illustrated through two examples with conclusive experimental results: a preliminary study made on a manikin with an arm exoskeleton controlling the movement (passive mode) and a larger campaign on ten healthy subjects performing pointing tasks with a transparent robot (active mode).

Robotic Exoskeletons: A Perspective for the Rehabilitation of Arm Coordination in Stroke Patients

Upper-limb impairment after stroke is caused by weakness, loss of individual joint control, spasticity, and abnormal synergies. Upper-limb movement frequently involves abnormal, stereotyped, and fixed synergies, likely related to the increased use of sub-cortical networks following the stroke. The flexible coordination of the shoulder and elbow joints is also disrupted. New methods for motor learning, based on the stimulation of activity-dependent neural plasticity have been developed. These include robots that can adaptively assist active movements and generate many movement repetitions. However, most of these robots only control the movement of the hand in space. The aim of the present text is to analyze the potential of robotic exoskeletons to specifically rehabilitate joint motion and particularly inter-joint coordination. First, a review of studies on upper-limb coordination in stroke patients is presented and the potential for recovery of coordination is examined. Second, issues relating to the mechanical design of exoskeletons and the transmission of constraints between the robotic and human limbs are discussed. The third section considers the development of different methods to control exoskeletons: existing rehabilitation devices and approaches to the control and rehabilitation of joint coordinations are then reviewed, along with preliminary clinical results available. Finally, perspectives and future strategies for the design of control mechanisms for rehabilitation exoskeletons are discussed.

A Framework to Describe, Analyze and Generate Interactive Motor Behaviors

While motor interaction between a robot and a human, or between humans, has important implications for society as well as promising applications, little research has been devoted to its investigation. In particular, it is important to understand the different ways two agents can interact and generate suitable interactive behaviors. Towards this end, this paper introduces a framework for the description and implementation of interactive behaviors of two agents performing a joint motor task. A taxonomy of interactive behaviors is introduced, which can classify tasks and cost functions that represent the way each agent interacts. The role of an agent interacting during a motor task can be directly explained from the cost function this agent is minimizing and the task constraints. The novel framework is used to interpret and classify previous works on human-robot motor interaction. Its implementation power is demonstrated by simulating representative interactions of two humans. It also enables us to interpret and explain the role distribution and switching between roles when performing joint motor tasks.

How can human motion prediction increase transparency

A major issue in the field of human-robot interaction for assistance to manipulation is transparency. This basic feature qualifies the capacity for a robot to follow human movements without any human-perceptible resistive forces. In this paper we address the issue of human motion prediction in order to increase the transparency of a robotic manipulator. Our aim is not to predict the motion itself, but to study how this prediction can be used to improve the robot transparency. For this purpose, we have designed a setup for performing basic planar manipulation tasks involving movements that are demanded to the subject and thus easily predictable. Moreover, we have developed a general controller which takes a predicted trajectory (recorded from offline free motion experiments) as an input and feeds the robot motors with a weighted sum of three controllers: torque feedforward, variable stiffness control and force feedback control. Subjects were then asked to perform the same task but with or without the robot assistance (which was not visible to the subject), and with several sets of gains for the controller tuning. First results seems to indicate that when a predictive controller with open loop torque feedforward is used, in conjunction with force- feedback control, the interaction forces are minimized. Therefore, the transparency is increased.

A versatile biomimetic controller for contact tooling and haptic exploration

This article presents a versatile controller that enables various contact tooling tasks with minimal prior knowledge of the tooled surface. The controller is derived from results of neuroscience studies that investigated the neural mechanisms utilized by humans to control and learn complex interactions with the environment. We demonstrate here the versatility of this controller in simulations of cutting, drilling and surface exploration tasks, which would normally require different control paradigms. We also present results on the exploration of an unknown surface with a 7-DOF manipulator, where the robot builds a 3D surface map of the surface profile and texture while applying constant force during motion. Our controller provides a unified control framework encompassing behaviors expected from the different specialized control paradigms like position control, force control and impedance control.

A Methodology to Quantify Alterations in Human Upper Limb Movement During Co-Manipulation With an Exoskeleton

While a large number of robotic exoskeletons have been designed by research teams for rehabilitation, it remains rather difficult to analyse their ability to finely interact with a human limb: no performance indicators or general methodology to characterize this capacity really exist. This is particularly regretful at a time when robotics are becoming a recognized rehabilitation method and when complex problems such as 3-D movement rehabilitation and joint rotation coordination are being addressed. The aim of this paper is to propose a general methodology to evaluate, through a reduced set of simple indicators, the ability of an exoskeleton to interact finely and in a controlled way with a human. The method involves measurement and recording of positions and forces during 3-D point to point tasks. It is applied to a 4 degrees-of-freedom limb exoskeleton by way of example.

Slaves no longer: review on role assignment for human-robot joint motor action

This paper summarizes findings on the growing field of role assignment policies for human–robot motor interaction. This topic has been investigated by researchers in the psychological theory of joint action, in human intention detection, force control, human–human physical interaction, as well as roboticists interested in developing robots with capabilities for efficient motor interaction with humans. Our goal is to promote fruitful interaction between these distinct communities by: (i) examining the role assignment policies for human–robot joint motor action in experimental psychology and robotics studies; and (ii) informing researchers in human–human interaction on existing work in the robotic field. After an overview of roles assignment in current robotic assistants, this paper examines key results about shared control between a robot and a human performing interactive motor tasks. Research on motor interaction between two humans has inspired recent developments that may extend the use of robots to applications requiring continuous mechanical interaction with humans.

Design and acceptability assessment of a new reversible orthosis

We present a new device aimed at being used for upper limb rehabilitation. Our main focus was to design a robot capable of working in both the passive mode (i.e. the robot shall be strong enough to generate human-like movements while guiding the weak arm of a patient) and the active mode (i.e. the robot shall be able of following the arm without disturbing human natural motion). This greatly challenges the design, since the system shall be reversible and lightweight while providing human compatible strength, workspace and speed. The solution takes the form of an orthotic structure, which allows control of human arm redundancy contrarily to clinically available upper limb rehabilitation robots. It is equipped with an innovative transmission technology, which provides both high gear ratio and fine reversibility. In order to evaluate the device and its therapeutic efficacy, we compared several series of pointing movements in healthy subjects wearing and not wearing the orthotic device. In this way, we could assess any disturbing effect on normal movements. Results show that the main movement characteristics (direction, duration, bell shape profile) are preserved.

A methodology to design kinematics of fixations between an orthosis and a human member

The design of robotic orthoses focuses strongly on replicating kinematics of human limb. However, often sophisticated mechanisms which attempt at reproducing complex kinematics of human joints fails in adapting to geometrical variations of subjects sizes and eccentricities. One major that arrises from this mismatching is an occurrence of hyperstaticity induced by the uncontrolled interaction forces. In this paper, we take the point of view of statics to investigate the force transmission problem, which is required for a fine force control. The main result of this study focuses on designing fixations between the orthosis and the human limb that provide additional degrees of freedom. The method involves two steps. Firstly, a set of possible solutions with respect to the isostaticity criterion is derived. Then, among these possible solutions, a set of design rules considering physiological aspects of transmitting forces to human limbs is used to select a preferred configuration. As an example, the method is applied to an existing 4 active DOF arm orthosis.

On the kinematic design of exoskeletons and their fixations with a human member

A crucial problem in developing robotic exoskeletons lies in the design of physical connexions between the device and the human limb it is connected to. Indeed, because in general the human limb kinematics and the exoskeleton kinematics differ, using an embedment at each connection point leads to hyperstaticity. Therefore, uncontrollable forces can appear atthe interaction port. To cope with this problem, literature suggests to add passive mechanisms at the fixation points. However, empirical solutions proposed so far suffer from a lack of proper analysis and generality. In this paper, we study the general problem of connecting two similar kinematic chains through multiple passive mechanisms. We derive a constructive method that allows to determine all the possible repartitions of freed DoFs across the different fixation mechanisms. It also provides formal proofs of global isostaticity. Practical usefulness is illustrated through an example with conclusive experimental results. I. I NTRODUCTION More and more exoskeletons are being designed by researchers for a growing number of applications, ranging fro m military applications [1] to rehabilitation [2]. For years, research has mainly focused on technological aspects (actuators, embedment, energy...) and followed a paradigm defined in [3]: ”an exoskeleton is an external structural mechanism with joints and links corresponding to thos e of the human body”. In other words, designing the kinematics of an exoskeleton generally consists of trying to replicate the human limb kinematics. This brings a number of advantages: similarity of the workspaces, singularity avoidance [4], o neto-one mapping of joint force capabilities over the workspa ce. The major drawback of this paradigm is that, in fact, human kinematics is impossible to precisely replicate with a robo t. Indeed two problems occur: morphology drastically varies between subjects and, for a given subject, the joints kinema tics is very complex and cannot be imitated by conventional robot joints [5]. In fact, it is impossible to find any consensual model of the human kinematics in the biomechanics literatur e due to complex geometry of bones interacting surfaces. For example, different models are used for the shoulder-scapul aclavicle group [6]. Discrepancies between the two kinematic chains thus seem unavoidable. Because of the connexions between multiple loops, it generates kinematic compatibility problems. Ind ee , when connecting two-by-two the links of two kinematically similar chains that are not perfectly identical, hyperstaticity occurs. This phenomenon leads, if rigid models are used, to the impossibility of moving and the appearance of noncontrollable (possibly infinite) internal forces. In pract ice, though, rigidity is not infinite and mobility can be obtained thanks to deformations. When a robotic exoskeleton and a human limb are connected, most likely, these deformations occ ur at the interface between the two kinematic chains, caused by the low stiffness of human skin and tissues surrounding the bones [7]. Solutions found in the literature to cope with this problem are of two kinds. In a first approach the exoskeleton design can be thought in such a way that adaptation to human limb kinematics is maximized. Robotic segments with adjustable length were thus developed, and pneumatic systems were added to introduce elasticity in the robot fixations and adaptability to variable limb section [8]. This minimizes t he kinematic differences, but drastically increases the comp lexity of the device, leading to weight increase, stiffness limita tions, etc. Furthermore, again, it seems that perfect matching at a ny instant is yet out of reach. The second approach consists in adding passive DoFs to connect the two kinematic chains. This was proposed back in the 1970s in the context of passive orthoses, [9], [10]. The same principle was recently proposed for a one degree of freedom device in [7], but the force transmission is analyze d only in a plane, and relies on explicit equations derived for a particular planar mechanism. It thus suffers from a lack of generality and the author neglects all the off-plane forc es that unavoidably arise from the unmodeled lack of paralleli sm between the human limb plane and the exoskeleton plane. Rather, the constructive method proposed here applies to a general spatial problem, which is properly formalized and t hen solved thanks to a set of necessary and sufficient conditions for global isostaticity (Section II). In Section III, the me thod is applied to ABLE, a given active 4DoF arm exoskeleton. In Section IV, experimental results illustrate the practical nterest of the approach. II. GENERAL METHODOLOGY The main question addressed in this paper is: given a proposed exoskeleton structure designed to (approximatel y) replicate a human limb kinematic model, how to connect it to the human limb while avoiding the appearance of uncontrollable forces at the interface? The answer takes the form of a set of passive frictionless mechanisms used to connect the robot and the subject’s limb that allows to avoid hyperstati city. A. Problem formulation We consider two different serial chains with multiple couplings as illustrated in Fig. 1. One represents a human limb H and the other the robot structure R. Fig. 1. Schematic of two serial chains parallel coupling The base body of the exoskeleton is supposed to be attached to a body of the human subject. This common body is denoted R0 ≡ H0. The robot and the limbs are supposed to be connected through n fixations. Each fixation is a mechanism L i for i ∈ {1, ..,n} consisting in a passive kinematic chain which connects a human body Hi to a robot bodyRi . Mechanisms L i are supposed to possess a connectivity l i . Recall that connectivity is the minimum and necessary number of joint scalar variables that determine the geometric configuratio n of the L i chain [11]. Typically,L i will be a nonsingular serial combination of l i one DoF joints. The fixation can be an embedment ( l i = 0) or can release several DoFs, such that: ∀i ∈ {1, ..,n} , 0≤ l i ≤ 5 . (1) Indeed choosingl i ≥ 6 would correspond to complete freedom betweenHi and Ri which would not make any practical sense in the considered application where force transmissi on is required. BetweenRi−1 and Ri , on the robot side, there is an active mechanismRi which connectivity is denotedr i . Similarly, betweenHi−1 andHi on the human side, there is a mechanism H i of connectivity hi . Note that, due to the complexity of human kinematichi is not always exactly known, and literature from biomechanics provides controversial data on this poin t. For example, the elbow is often modeled as a one DoF joint, but in reality a residual second DoF can be observed [12]. Our goal is to design mechanisms L i with i ∈ {1, ..,n} in such a way that on one side, all the forces generated by the exoskeleton on the human limb are controllable and on the other side, there is no possible motion for the exoskeleton when the human limb is still. We shall thus consider in the next that the human limbs are virtually attached to the base body R0. This represents the case, when the subject does not move at all. The resulting mechanism, depicted in Fig. 2, is denotedSn. Fig. 2. Studied problem with a fixed human limb A proper design for the passive mechanisms L i hall guarantee that, in the absence of any external forces, both: ∀i ∈ 1· · ·n, nTi = {0} and (2a) ∀i ∈ 1· · ·n, nWL i→0 = {0} , (2b) wherenTi is the space of twists describing the velocities of robot bodyRi relative toR0 when the whole mechanismSn is considered andnWL i→0 is the space of wrenches (forces and moments) statically admissible transmitted through th e L i chain on the reference body R0, when the whole mechanism Sn is considered. Equation (2a) expresses the fact that the mobility of any rob ot body connected to a human limb should be null, which is required since the human member is supposed here to be still. Moreover, Eq. (2b) imposes that, considering the who le mechanism, there can be no forces of any kind exerted on the human limb. Indeed, since the actuators are supposed to apply null generalized forces, the presence of any force at the connection ports would be an uncontrollable force due to hyperstaticity. In the next Eq. (2) is referred as the global isostaticity condition. B. Conditions on the twist space ranks At first, one can notice the recursive structure of the consid ered system: if we name Si the sub-mechanism constituted by the bodiesR0 to Ri , the chainsR0 to Ri andL0 to L i , we can representSi recursively fromSi−1, as in Fig. 3, wheremi−1 Fig. 3. Recursive structure Si of the system is the connectivity ofSi−1. In this convention,S0 represents a zero DoF mechanism. Using this recursive representation on e can establish the following proposition: Proposition 1: The conditions (2) are equivalent to : ∀i ∈ 1· · ·n, dim(TSi−1 +TRi +TL i ) = 6 and (3a) ∀i ∈ 1· · ·n, dim(TSi−1 ∩TRi ) = 0 and (3b) dim(TSn) = 0 , (3c) where TSj = Sj Tj is the space of twists describing the velocities ofR j relative toR0, whenSj is considered isolated from the rest of the mechanism (then it is different from nTj ), TRi is the space of twists produced by Ri – i.e. the space of twists of Ri relative toRi−1 if they were only connected throughRi , TL i is the space of twists produced by L i i.e. the space of twists of Ri relative toR0 if they were only connected throughL i . The demonstration can be found in Appendix A. Remarkably, conditions (3) involve the space of twists gene rated byRi andL i when taken isolated, which is of great help for design purposes. In the next, we convert these condition s into constraints on the connectivities r i = dim(TRi ) and l i = dim(TL i ). To do so, we suppose that kinematic singularities are avoided. In other words, summing the subspaces of twists wil l always lead to a subspace of maximum dimension given the dimensi