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Road safety relies mostly on available tire to road grip regarding to the forces required by a vehicle in a given dynamic situation. For example safety issues can occur when deceleration required forces exceeding the tire/road grip potential. Issues are much critical while traveling in a curve with a coupled longitudinal/transverse grip demand. Instrumented vehicles can be used in order to evaluate the available tire to road grip in rolling situations, but it remains linked to a dedicated vehicle and models have to be use to extrapolate these evaluations to various vehicles. The aim of this work is to propose a sensor embedded in the road infrastructure to evaluate the longitudinal and transverse grip demand of any traveling vehicle. A 6 axis sensor is embedded in a road test track, under a piece of the real road upper layer. Measurement are made at a acquisition rate of 2500 Hz and forces measuring ranges are of 2500 daN (vertical axis) and 750 daN (tangential). Measurements are compared to on-board measurement with a vehicle instrumented with dynamometric wheels. Three situations are experienced in a 100 meters curve: traveling at a given speed and traveling while accelerating or braking moderately, and for three vehicle speeds of 40, 60 and 80 km/h. Force evaluation from the two systems are differing of only 5% for the vertical force and 10% for the tangential forces. The differences are lower for the higher grip demands. For example moderate braking from 70 km/h in curve lead to 0.23 and 0.25 longitudinal friction coefficients (LFC) for road sensor and dynamometric wheel, and to 0.17 and 0.19 transversal friction coefficients (TFC). In perspectives, evaluations of an excessive grip demand could result in solutions as lowering the designed speed or improving the road surface layer.

The French metropolis, Rouen Normandie, has a project of a new bridge requiring temporary pier in the river Seine during the building phase. The location of this pier in the river is constrained by mechanical reasons related to the construction of the bridge. The purpose of this study is to find a position of this pier in the mechanically constrained area which minimizes vessel traffic obstruction and therefore collision risk. This type of study is classically carried out by using complex and multiple vessel dynamics simulation software in order to assess the risk for a given vessel to crash into the pier. The novelty of this study is to propose a statistical study based on the database of Automatic Identification System (AIS) of the Vessel Traffic Service (VTS) that is an automatic tracking system relying on ships transceivers. The technical objective is to identify low risk areas according to vessel speeds and sizes. Both factors should have an impact on the maneuverability of ships to avoid pier collision risk. Among all trajectories, straight line trajectories are selected based on statistical methods. The computation of prediction intervals of these trajectories delimits navigation zone. If all the straight trajectories are taken into account, the navigation zone extends to the whole river surface, which is not an helping result. However, by focusing on large and high speed vessels trajectories the navigation zone of these weak maneuverable ships is more centered in the middle of the river and represents only 25% of the river area. The complement of this area delineates possible locations of the temporary pier of the bridge in the river that do not disrupt vessel traffic.

Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle’s technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

Energy consumed by road vehicles has a high impact on climate changes; indeed this energy use accounts for 23% of total energy-related Green House Gases (GHG) emissions of 2014 global GHG emissions. GHG emissions are growing constantly year after year, in spite of global objectives (COP) and researches on vehicle efficiency and modal shift. The contribution of the infrastructure to lower this energy is less studied, since it is often seen as immuable or too costly. This paper aims to demonstrate that simple and low-cost solutions exist for that purpose. Particularly a methodology has been developed, based on an optimization of the speed layout over an itinerary in order to improve the eco- driving potential of a given road infrastructure. The key point of this work is that inconsistency often exists between vehicle dynamics, road longitudinal profile and changes in regulation speeds. These changes in speed are defining the speed- sectioning of a route, and an optimization of this speed-sectioning can be easily carried out while displacing or modifying speed signs. The objective of this study is to build an optimized speed sectioning which minimizes the fuel consumption for realistic traffic and various driver behaviors, while maintaining the required safety levels. A progressive optimization loop has been worked out with a Python script including an embedded microscopic road traffic simulator. As a result, an optimized speed-sectioning is leading to a gain of 227 ml for 60 minutes of simulated flow of 100 veh/h/lane, for a modification of a single speed changing point. The overall benefits are reduced energy consumption, air pollution and noise which otherwise would have been produced by braking. This work brings an effective optimization tool for road managers and its practical application is passive and inexpensive. This methodology is suitable for rural and urbanized territories and easily adaptable to any type of traffic in various countries. In perspectives, the optimization process could be extended to a full road route and to a wide range of different speed-sectioning layouts.

CETRA 2020, 6th International Conference on Road and Rail Infrastructure - Online, Pula, CROATIE, 20-/05/2021 - 21/05/2021; In a context of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. In a previous study, a gain of 5% in the spent energy was estimated on specific route by slightly moving some speed signs, but under the assumptions that drivers practice eco-driving and the traffic is free-flow. This paper deepens and widens these first results. The base of this research is to provide a simulation model to study the impact of traffic and speed-sectioning on the environment. Inside this model, the impact of different approach speeds to a speed-sectioning is assessed. The simulation is conducted within the Trafficware Synchro environment where parameters according to road infrastructure, vehicle and driver are based on real traffic data. Moving a speed limitation sign can contribute to a reduction of fuel consumption up to 8% depending on driver structure. This new methodology improves the accuracy of our first results and detects adverse effects as the possible emergence of congestion due to the modification of speed sectioning. In perspective this methodology represents a significant argument in road managers strategy. In addition it also represents an orienting point to investigate different action scenarios and a first step to a global optimization policy in managing road infrastructure.

This paper proposes a methodology to optimize the longitudinal profile of roads according to either an energy consumption or Global Warming Potential (GWP) criterion calculated for both construction and operation phases. For the construction phase assessment, this methodology is based on a earthworks model that computes the geometric differences between the natural terrain and the longitudinal road profile and moreover uses environmental data validated with real experiments. The operation phase is assessed by simulating traffic over a ten-years period. Traffic simulations are based on vehicle dynamic models, also validated with real experiments. The optimization problem is set up in a finite dimensional optimization. A case study illustrates this methodology. By taking into account actual traffic measurements, the optimized profile decreases by 6% the total primary energy consumption and by 8% the GWP.

Analyzing spatial structures of transportation data at various scales can be of prime interest to transportation planning and governance. In recent years, multi-scale spatial analysis methods have been developed and used in fields like ecology and geography, but only a few studies have applied these methods to transportation data. However, such methods can provide an efficient exploratory tool for: identifying those scales at which transportation data vary spatially; modeling the spatial structures at each scale; and determining the processes at work that explain these spatial structures. This paper describes and demonstrates how a multi-scale spatial analysis method, namely distance-based Moran's eigenvector maps (dbMEM), can be applied to study the spatial layout of car ownership. For this analysis, we rely on aggregated census data for small statistical areas within France's Loire-Atlantique administrative region. At first, 176 spatial vectors representing spatial patterns with a positive autocorrelation are constructed. Among the 176 vectors, only 23 significant ones are retained after performing a regression with car ownership as the dependent variable. Next, we divide these spatial vectors into three sub-models representing three spatial scales: broad scale, medium scale, and fine scale. Lastly, we identify a set of sociodemographic factors capable of explaining the spatial variation at each scale, i.e.: the broad-scale variation is mainly explained by population density, couples with children and income variables; the medium scale by couples with children, share of individuals in the 25–54 year age range and income; and the fine scale by couples with children and income variables.

TIS Roma 2019, AIIT 2nd International Congress on Transport Infrastructure and Systems in a changing world, ROME, ITALIE, 23-/09/2019 - 24/09/2019; Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle's technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

5th International Conference on Road and Rail Infrastructure (CETRA 2019), ZADAR, CROATIE, 17-/05/2018 - 19/05/2018; Eco-driving is an efficient way to preserve energy resources and limit environment impacts. It is first of all a question of driver behaviour and motivation, vehicle characteristics, but infrastructure parameters could favour - or impede- ecodriving. This study aims to qualify this infrastructure influence, for the speed sectioning parameter of roads. A research evaluating the adequacy between speed changes along a route, vehicle dynamics and the road gradient constitute the frame of this work. Indeed this adequacy has been proven to be descriptive of the ecodriving potentiality of a route, as detailed in a previous experimental evaluation in France (Coiret et al [8]). It is reinforced here with the help of experimental evaluation in Bosnia, with a metro-logical reinforcement : differential gps, temporal tagging system at points of interest, roof anemometer for the influence of wind, is now used to have more accurate data. In particular the better altitude measurements increase results quality, with achievable reductions of 5 % of energy consumptions for given route sections with sectioning optimisation (ie : simple speed limit panels repositioning) We have also researched crucial points on how to compare different countries and their legislation, geography, and traffic conditions. Bosnia and Herzegovina and France are in the context, to indicate that an assessment of quality level in eco-driving of the two countries is taken in consideration. Perspectives are given in terms of traffic software generalization of the experimental results and in terms of speed sectioning revisions in order to reduce linked energy losses and CO2 emissions. A route model could then be evaluated, for which speed-sectioning and positioning of amenities (speed bumper, traffic lights) could be optimized in energy use of infrastructure, with a concern not to alter the security features.

This paper deals with the important topic of rigid industrial robots identification. The usual identification method is based on the use of the inverse dynamic model and the least-squares technique. In order to obtain good results, a well-tuned derivative bandpass filtering of joint positions is needed to calculate the joint velocities and accelerations. However, we can doubt whether the bandpass filter is well-tuned or not. Another approach is the instrumental variable (IV) method which is robust to data filtering and which is statistically optimal. In this paper, an IV approach relevant for identification of rigid industrial robots is introduced. The set of instruments is the inverse dynamic model built from simulated data which are calculated from the simulation of the direct dynamic model. The simulation assumes the same reference trajectories and the same control structure for both the actual and the simulated robot and is based on the previous IV estimates. Furthermore, to obtain a rapid convergence, the gains of the simulated controller are updated according to IV estimates. Thus, the proposed approach validates the inverse and direct dynamic models simultaneously and is not sensitive to initial conditions. The experimental results obtained with a 2 degrees of freedom (DOF) planar prototype and with a 6 DOF industrial robot show the effectiveness of our approach: it is possible to identify 60 parameters in 3 iterations and in 11 s.

International audience; In this paper, a presentation of Tchebychev polynomials’ properties and a formulation derived using these polynomials are performed. The identification method presented consists in applying a linear transformation to the set of equations of the process. For this, the mathematical operator used is based on a decomposition of the signal in a basis of orthogonal polynomials. We show that this projection acts as a bandpass filter, so that only one operation is required for the data preprocessing before the identification, namely the choice of the Chebyshev polynomials basis size. An experimental closed-loop identification of a 2-axis robot with this method is performed in a final section. The results are compared and analyzed with other techniques used in robotics.; Dans cet article, une présentation des propriétés des polynômes de Tchebychev et une formulation dérivée utilisant ces polynômes sont effectuées. La méthode d'identification présentée consiste à appliquer une transformation linéaire sur le système d'équations qui régit le processus. Pour cela, l'opérateur mathématique utilisé s'appuie sur une décomposition du signal dans une base formée de polynômes orthogonaux. Nous montrons que cette projection se comporte comme un filtre passe-bande, de telle sorte qu'une seule opération est nécessaire pour le pré-traitement des données avant le processus d'identification, à savoir choisir la dimension de la base des polynômes Tchebychev. Une identification expérimentale en boucle fermée d'un robot à 2 axes avec cette méthode est effectuée dans une dernière partie. Les résultats obtenus sont comparés et analysés avec d'autres techniques utilisées en robotique.

International audience; This paper deals with joint stiffness identification with a new Closed-Loop Output Error (CLOE) method which minimizes the quadratic error between the actual motor force/torque and the simulated one. This method is based on the DIDIM (Direct and Inverse Identification Model) procedure which has been validated on rigid robots and which is now applied to a flexible joint robot. DIDIM method requires a gain updating in the simulated robot in order to keep the bandwidth of the rigid controlled degree of freedom (dof ) and to keep the natural frequency of the flexible dof, close to the actual ones, at each step of the recursive Gauss Newton non linear programming algorithm. This gain updating requires a first step of estimating the natural frequency of the flexible dof before applying DIDIM method in a second step. An experimental setup exhibits identification results and shows the effectiveness of our approach.

The identification of the dynamic parameters of robot is based on the use of the inverse dynamic model which is linear with respect to the parameters. This model is sampled while the robot is tracking “exciting” trajectories in order to get an over determined linear system. The linear least squares solution of this system calculates the estimated parameters. The efficiency of this method has been proved through the experimental identification of a lot of prototypes and industrial robots. However, this method needs joint torque and position measurements and the estimation of the joint velocities and accelerations through the pass band filtering of the joint position at high sample rate. So, the observation matrix is noisy. Moreover identification process takes place when the robot is controlled by feedback. These violations of assumption imply a theoretical biased LS solution which can be avoided with prefiltering data and tracking “exciting” trajectories. The Simple Refined Instrumental Variable (SRIV) approach deals with this problem of noisy observation matrix and can be statistically optimal. This paper focuses on this technique which will be applied to a 2 degrees of freedom (DOF) prototype developed by the IRCCyN Robotic team.

The identification of the dynamic parameters of robot is based on the use of the inverse dynamic model which is linear with respect to the parameters. This model is sampled while the robot is tracking trajectories which excite the system dynamics in order to get an over determined linear system. The linear least squares solution of this system calculates the estimated parameters. The efficiency of this method has been proved through the experimental identification of a lot of prototypes and industrial robots. However, this method needs joint torque and position measurements and the estimation of the joint velocities and accelerations through the pass band filtering of the joint position at high sample rate. The new method needs only torque data at a low sample rate. It is based on a closed loop simulation which integrates the direct dynamic model. The optimal parameters minimize the 2 norm of the error between the actual torque and the simulated torque assuming the same control law and the same tracking trajectory. This non linear least squares problem is dramatically simplified using the inverse model to calculate the derivatives of the cost function.

Pierre-Olivier received the B. Sc and the M. Sc in applied mathematics from the Paris-Dauphine University (Paris, 1990). He graduated, as a civil engineer, from Ecole des Mines de Paris (Paris, 1992) . He received the Ph. D degree from both the Ecole des Mines de Paris and the French Atomic Agency (CEA) (1995). He has been researcher with the French institute of sciences and technology for transport, development and networks (Ifsttar) since 1997 where its research is based on contracts (European projects : Circ, Osyris, Intro, French project : Cervifer, contracts with Ermont, Eurovia, Ratp, Renault, RMC, SNCF, Tisséo), Le fil conducteur de ma recherche est l'application des techniques robotiques en identification des modèles inverses aux systèmes de transport routier et ferroviaire. Mes compétences scientifiques sont dans le domaine des mathématiques appliquées : statistiques, analyse numérique matricielle, théorie de la viabilité.Travaillant dans un organisme de recherches finalisées, ces compétences ont étémises en oeuvre pour résoudre des questions pratiques- souleÎes par les chantiers du génie civil : estimation du torseur des efforts de contact lors du compactage des enrobés, évaluation de différents systèmes de malaxage des bétons [10] ;- provenant de la sécurité routière : mesures de la courbe reliant le taux de glissement au frottement pneumatique/chaussée d'un Îhicule routier en freinage [1], évaluation de l'état d'un Îhicule en conduite apaisée[9],- en écoconception : évaluation de la consommation des trains circulant sur une ligne à grande vitesse [2], établissement des fiches horaires pour les conducteurs (article accepté).Ces problèmes pratiques - ont nécessité des expérimentations de grandes ampleurs : 50 % de mes publications sont liés à des expérimentations que j'ai souvent organisées ;- ont dépassé mon champ disciplinaire : tous mes travaux sont effectués en collaboration avec d'autres laboratoires et avec des industriels.D'un point de vue théorique, j'ai contribué à l'établissement des méthodes d'identifications : IDIM-LS, IDIM-IV, DIDIM. ([3, 5, 6, 7, 4, 8]). Une contribution théorique complètement différente et fortuite est l'introduction des concepts issus de la théorie de la viabilité en sécurité routière [9].Mon activité de recherche en terme d'encadrement et de publications.Publications : 10 revues, 1 brevet (français et mondial), 29 congrès internationaux sur article dont 22 Ifac-Ieee, 11 congrès internationaux sur résumé,5 revues techniques francophones, 7 congrès francophones.Encadrement de thèses et de post-doctorant : 1,88 sur 4 thèses (3 Bourses Cifre,1/2 Bourse Région, 1/2 Bourse Ifsttar), 1 post-doctorant (financé sur projet Européen).

This paper deals with the dynamic modelling of a vibratory asphalt compactor. A compactor is a machine of road building site. The aim of the study is to estimate contact efforts between the drums of the compactor and asphalt. Robotic formalism is used to model the compactor as an articulated mechanical system. This robotic model is adapted to our system of measurement. In this way, it is sufficient to model drums to estimate contact efforts. The model is linear according to a set of dynamic parameters which can be identified using a Weighted Least Squares method. The identification is carried out through dedicated experiments where contact efforts were known. Thus, parameters are identified. During a real worksite, it has been possible for the first time to estimate contact efforts applied by a compactor.

This paper deals with the dynamic modelling of a vibratory asphalt compactor. A compactor is a machine of road building site. Its task is to increase the density of the asphalt. The aim of the study is to measure contact forces wrenches between the drums of the compactor and the bituminous mix. These drums vibrate. Traditional techniques of robotics are used to model the compactor as an articulated mechanical system. In order to reach our objective, the dynamic model is limited to the clamp-drum unit. Moreover, this model is adapted to our system of measurements by replacing some lagrangian variables by some Euler variables. In this manner, it is proved that it is possible to get the contact forces wrench. During a real worksite, it has been possible for the first time to measure the contact forces applied by a compactor.

This paper deals with the identification of adynamic model of a compactor. This model is linear in relation to a set of dynamic parameters which can be identified using a Weighted Least Squares method. With this method, the measurement of the trajectory must be accurate enough. In order to respect this accuracy in an industrial environnement, a specific data processing, based on cubic spline interpolation, as been developed to compute the trajectory of the compactor from the device mounted on standard compactors.

International audience; This brief deals with the identification of industrial robots. The usual identification method is based on the use of the inverse dynamic identification model and the least-squares technique. Another approach is the direct and inverse dynamic identification models (DIDIM) method, which is a closed-loop output error (CLOE) method minimizing the quadratic error between the actual and simulated joint torques. In this brief, the DIDIM method is compared with the usual CLOE method, which minimizes the quadratic error between the actual and simulated joint positions. The comparison is carried out on six degrees of freedom industrial robot. The experimental results show that the DIDIM method needs three iterations to identify 60 parameters while the usual CLOE method needs 20 iterations.

This paper deals with the topic of robots dynamics identification. In this paper, we focus on the instrumental variable (IV) technique. For robots, the set of instruments is the inverse dynamic model built from simulated data which are calculated from the integration of the direct dynamic model, assuming the same reference trajectories and the same control law structure for both actual and simulated robots. The integration of the direct dynamic model is based on previous IV estimates. This defines an iterative algorithm. Furthermore, gains of the simulated controller are updated to get a fast convergence. Experimental results obtained on a six degrees of freedom robot manufactured by Staubli show the effectiveness of our approach: 60 dynamic parameters are estimated in only two iterations.

Off-line robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to estimate the parameters. This method requires the joint force/torque and position measurements and the estimate of the joint velocity and acceleration, through the bandpass filtering of the joint position at high sampling rates. Recently, the DIDIM method has been proposed and validated on a 2 degree-of-freedom robot. DIDIM method requires only the joint force/torque measurement. It is a closed-loop output error (CLOE) method based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of the control law, and the same reference trajectory for both the actual and the simulated robot. The optimal parameters minimize the 2-norm of the error between the actual force/torque and the simulated force/torque. A validation experiment on a 6 dof Staubli TX40 robot shows that DIDIM method is very efficient on industrial robots.

International audience; This paper deals with joint stiffness identification with only actual motor force/torque data instead of motor and load positions. The parameters are estimated by using the DIDIM method which needs only input data. This method was previously validated on a 6 DOF rigid robot and is now extended to flexible systems. The criterion to be minimized is the quadratic error between the measured actual motor force/torque and the simulated one. The optimal parameters are calculated with the Nelder - Mead simplex algorithm. An experimental setup exhibits the experimental identification results and shows the effectiveness of our approach.

Tyre-road estimation methods have been the objective of many research programmes throughout the world. Most of these methods aim at estimating the friction components such as tyre longitudinal slip rate κ and friction coefficient μ in the contact patch area. In order to estimate the maximum available friction coefficient μmax , these methods generally use a probabilistic relationship between the grip obtained for low tyre excitations (such as constant speed driving) and the grip obtained for high tyre excitations (such as emergency braking manoeuvre). Confirmation or invalidation of this relationship from experimental results is the purpose of this paper. Experiments have been carried out on a reference track including several test boards corresponding to a wide textural spectrum. The main advantage of these experiments lies in the use of a vehicle allowing us to accurately build point-by-point relationship between κ and μ. This relationship has been determined for different tyres and pavement textures. Finally, the curves obtained are analysed to check the validity of the relationship between the current friction coefficient used by the car during normal driving conditions and μmax.

Offline robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to estimate the parameters. The efficiency of this method has been proved through the experimental identification of many prototypes and industrial robots. However, this method requires the joint force/torque and position measurements and the estimate of the joint velocity and acceleration, through the bandpass filtering of the joint position at high sampling rates. The proposed new method called DIDIM requires only the joint force/torque measurement, which avoids the calculation of the velocity and acceleration by bandpass filtering of the measured position. It is a closed-loop output error method where the usual joint position output is replaced by the joint force/torque. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of the control law, and the same reference trajectory for both the actual and the simulated robot. The optimal parameters minimize the 2-norm of the error between the actual force/torque and the simulated force/torque. This is a nonlinear least-squares problem which is dramatically simplified using the inverse dynamic model to obtain an analytical expression of the simulated force/torque, linear in the parameters. A validation experiment on a two degree-of-freedom direct drive rigid robot shows that the new method is efficient.

Usually, the identification of the dynamic parameters of robot makes use of the inverse dynamic model which is linear with respect to the parameters. This model is sampled while the robot is tracking exciting trajectories. This allows using linear least squares (LS) techniques to estimate the parameters. The efficiency of this method has been proved through experimental identifications of a lot of prototypes and industrial robots. However, it is known that LS estimators are sensitive to outliers and leverage points. Thus, it may be helpful to verify their reliability. This is possible by using robust regressions and residual analysis. Then, we compare the results with those obtained with classical LS regression. This paper deals with this issue and introduces the experimental identification and residual analysis of an one degree of freedom (DOF) haptic interface using the Huber's estimator. To verify the pertinence of our analyses, this comparison is also performed on a medical interface consisting of a complex mechanical structure.