, Since our defined derivatives map tangent Cartesian spaces, and these spaces coincide for the 3D rotation manifolds of S 3 and SO(3), i.e., ? = log(q) = log(R)

S. Agarwal, Keir Mierle and Others, Ceres Solver, vol.68, p.56

P. Agarwal, A. Gupta, G. Verma, H. Verma, A. Sharma et al., Wireless Monitoring and Indoor Navigation of a Mobile Robot Using RFID, Nature Inspired Computing, p.13, 2018.

S. Sunghwan-ahn and . Yoon, Seungyong Hyung, Nosan Kwak and Kyung Shik Roh. On-board odometry estimation for 3D vision-based SLAM of humanoid robot, Intelligent Robots and Systems (IROS), 2012.

, IEEE/RSJ International Conference on, p.53, 2012.

. Benjamin-baruch-aisen, An inertial measurement-based gait detection system for active leg prostheses, vol.125, 2007.

M. Angermann, P. Robertson, T. Kemptner, and M. Khider, A high precision reference data set for pedestrian navigation using foot-mounted inertial sensors, Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on, pp.1-6, 2010.

M. Angermann and P. Robertson, Footslam: Pedestrian simultaneous localization and mapping without exteroceptive sensors-hitchhiking on human perception and cognition, Proceedings of the IEEE, vol.100, p.66, 2012.

D. Atchuthan, A. Santamaria-navarro, N. Mansard, O. Stasse, and J. Solà, Odometry Based on Auto-Calibrating Inertial Measurement Unit Attached to the Feet, European Control Conference, vol.7, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01818697

A. Azarbayejani and A. P. Pentland, Recursive estimation of motion, structure, and focal length, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, issue.6, pp.562-575, 1995.

B. Barshan and H. , Inertial navigation systems for mobile robots, IEEE Transactions on Robotics and Automation, vol.11, issue.3, pp.328-342, 1995.

T. Beravs, J. Podobnik, and M. Munih, Three-axial accelerometer calibration using Kalman filter covariance matrix for online estimation of optimal sensor orientation, IEEE Transactions on Instrumentation and Measurement, vol.61, issue.9, p.48, 2012.

E. Bestaven, E. Guillaud, and J. Cazalets, Is "circling" behavior in humans related to postural asymmetry, PloS one, vol.7, issue.9, p.43861, 2012.

E. Floyd, A. Bloom, and . Lazerson, Laura Hofstadteret al. Brain, mind, and behavior, vol.1, 1988.

M. Bortole, A. Venkatakrishnan, F. Zhu, C. Juan, G. E. Moreno et al., The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study, Journal of neuroengineering and rehabilitation, vol.12, issue.1, p.54, 2015.

M. Brossard, S. Bonnabel, and J. Condomines, Unscented Kalman filtering on Lie groups, Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on, pp.2485-2491, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01489204

L. Bruno and P. Robertson, Wislam: Improving footslam with wifi, Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on, p.66, 2011.

J. Carpentier, S. Tonneau, M. Naveau, O. Stasse, and N. Mansard, A versatile and efficient pattern generator for generalized legged locomotion, Robotics and Automation (ICRA), 2016.
URL : https://hal.archives-ouvertes.fr/hal-01203507

, IEEE International Conference on, vol.116, p.54, 2016.

J. Carpentier, A. D. Prete, S. Tonneau, T. Flayols, F. Forget et al., Multi-contact Locomotion of Legged Robots in Complex Environments -The Loco3D project, RSS Workshop on Challenges in Dynamic Legged Locomotion, vol.116, p.115, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01543060

J. Carpentier, F. Valenza, and N. Mansard, Pinocchio: fast forward and inverse dynamics for poly-articulated systems, p.74, 2015.

D. Caruso, A. Eudes, M. Sanfourche, D. Vissière, and G. Le-besnerais, Robust indoor/outdoor navigation through magnetovisual-inertial optimization-based estimation, Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on, pp.4402-4409, 2017.

F. Chaumette, P. Rives, and B. Espiau, Positioning of a robot with respect to an object, tracking it and estimating its velocity by visual servoing, IEEE International Conference on, pp.2248-2253, 1991.

R. and O. Aycard, Multiple sensor fusion and classification for moving object detection and tracking, IEEE Transactions on Intelligent Transportation Systems, vol.17, issue.2, p.119, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01241846

D. Chdid, R. Oueis, H. Khoury, D. Asmar, and I. Elhajj, Inertial-vision sensor fusion for pedestrian localization, Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on, p.66, 2011.

, Automatic calibration for inertial measurement unit, Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on, p.48, 2012.

G. S. Chirikjian, Analytic Methods and Modern Applications of Applied and Numerical Harmonic Analysis. Birkhäuser" Basel, vol.2, 2012.

A. Chiuso, P. Favaro, H. Jin, and S. Soatto, Structure from motion causally integrated over time, IEEE transactions on pattern analysis and machine intelligence, vol.24, p.16, 2002.

Y. Seong, C. Cho, and . Park, A Calibration Technique for a Redundant IMU Containing Low-Grade Inertial Sensors, ETRI journal, vol.27, issue.4, p.48, 2005.

A. Codas, M. Devy, and C. Lemaire, Robot localization algorithm using odometry and RFID technology, IFAC Proceedings Volumes, vol.43, p.13, 2010.

E. Andrew-i-comport, P. Malis, and . Rives, Real-time quadrifocal visual odometry, The International Journal of Robotics Research, vol.29, issue.2-3, pp.245-266, 2010.

A. Day and G. Singer, Real-time simultaneous localisation and mapping with a single camera, Journal of Experimental Psychology, vol.68, issue.17, p.337, 1964.

J. Varuna-de-silva, A. Roche, and . Kondoz, Fusion of Li-DAR and camera sensor data for environment sensing in driverless vehicles, p.119, 2017.

F. Dellaert and M. Kaess, Square Root SAM: Simultaneous localization and mapping via square root information smoothing, The International Journal of Robotics Research, vol.25, issue.12, p.29, 2006.

P. Mwm-gamini-dissanayake, H. F. Newman, S. Durrant-whyte, M. Clark, and . Csorba, An experimental and theoretical investigation into simultaneous localisation and map building, Experimental robotics VI, p.27, 2000.

R. Douc and O. Cappé, Comparison of resampling schemes for particle filtering, ISPA 2005. Proceedings of the 4th International Symposium on, p.27, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00005883

A. Doucet, S. Godsill, and C. Andrieu, On sequential Monte Carlo sampling methods for Bayesian filtering, Statistics and computing, vol.10, issue.3, pp.197-208, 2000.

A. Doucet, D. Nando, N. Freitas, and . Gordon, An introduction to sequential Monte Carlo methods, Sequential Monte Carlo methods in practice, pp.3-14, 2001.

E. Eade, Lie Groups for 2D and 3D Transformations

E. Eade and T. Drummond, Scalable monocular SLAM, Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.1, p.12, 2006.

E. Eade, Lie groups for 2d and 3d transformations, vol.88, 2013.

A. Garry, . Einicke, and . Langford-b-white, Robust extended Kalman filtering, IEEE Transactions on Signal Processing, vol.47, issue.9, pp.2596-2599, 1999.

F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers et al., An evaluation of the RGB-D SLAM system, Robotics and Automation (ICRA), 2012 IEEE International Conference on, p.28, 2012.

A. Esquenazi, M. Talaty, A. Packel, and M. Saulino, The ReWalk powered exoskeleton to restore ambulatory function to individuals with thoracic-level motor-complete spinal cord injury, American journal of physical medicine & rehabilitation, vol.91, issue.11, pp.911-921, 2012.

]. Hr and E. , Sensors for mobile robots, 1995.

D. Seyed-abolfazl-fakoorian, H. Simon, V. Richter, and . Azimi, Ground reaction force estimation in prosthetic legs with an extended Kalman filter, Systems Conference (SysCon), pp.1-6, 2016.

F. Maurice, M. Fallon, N. Antone, S. Roy, and . Teller, Drift-free humanoid state estimation fusing kinematic, inertial and lidar sensing, 14th IEEE-RAS International Conference on, vol.76, p.53, 2014.

R. Featherstone, Rigid body dynamics algorithms, p.74, 2014.

S. K. Wt-fong, A. Ong, and . Nee, Methods for in-field user calibration of an inertial measurement unit without external equipment, Measurement Science and technology, vol.19, issue.8, p.48, 2008.

C. Forster and L. Carlone, Frank Dellaert and Davide Scaramuzza. IMU preintegration on manifold for efficient visual-inertial maximum-a-posteriori estimation, Robotics: Science and Systems. Georgia Institute of Technology, vol.55, p.61, 2015.

C. Forster and L. Carlone, Frank Dellaert and Davide Scaramuzza. On-Manifold Preintegration for Real-Time Visual-Inertial Odometry, 2016.

C. Forster and L. Carlone, Frank Dellaert and Davide Scaramuzza. On-Manifold Preintegration for Real-Time Visual-Inertial Odometry, IEEE Transactions on Robotics, vol.33, issue.1, pp.1-21, 2017.

, Eric Foxlin. Pedestrian tracking with shoe-mounted inertial sensors, IEEE Computer graphics and applications, vol.25, issue.6, p.68, 2005.

T. Germa and F. Lerasle, Noureddine Ouadah and Viviane Cadenat. Vision and RFID data fusion for tracking people in crowds by a mobile robot, Computer Vision and Image Understanding, vol.114, issue.6, p.27, 2010.

K. Walter-d-glanze, L. E. Anderson, and . Anderson, Mosby's medical, nursing, and allied health dictionary. Mosby, 1994.

H. Gene, C. Golub, and . Loan, Matrix computations, p.37, 2012.

L. Goncalves, E. D. Bernardo, D. Benson, M. Svedman, J. Ostrowski et al., A visual frontend for simultaneous localization and mapping, Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pp.44-49, 2005.

]. Gonzalez, LOGIMATIC: Tight integration of EG-NSS and on-board sensors for port vehicle automation, p.2016, 2016.

G. Grisetti, C. Stachniss, and W. Burgard, Improved techniques for grid mapping with rao-blackwellized particle filters, IEEE transactions on Robotics, vol.23, issue.1, p.27, 2007.

G. Grisetti, C. Stachniss, S. Grzonka, and W. Burgard, A Tree Parameterization for Efficiently Computing Maximum Likelihood Maps using Gradient Descent, Robotics: Science and Systems, vol.3, p.29, 2007.

D. Paul, . Groves, W. Graham, A. Pulford, . Littlefield et al., Inertial navigation versus pedestrian dead reckoning: Optimizing the integration, Proc. ION GNSS, pp.2043-2055, 2007.

T. Hamel, E. Robert, and . Mahony, Direct Inertial Measurements. In ICRA, p.41, 2006.

M. Hardegger, D. Roggen, S. Mazilu, and G. Tröster, ActionSLAM: Using location-related actions as landmarks in pedestrian SLAM, Indoor Positioning and Indoor Navigation (IPIN), 2012.

, International Conference on, p.66, 2012.

R. Hartley, G. Maani, L. Jadidi, J. Gan, J. W. Huang et al., Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation within Factor Graphs, 2018.

D. Jeroen and . Hol, Sensor fusion and calibration of inertial sensors, vision, ultra-wideband and GPS, p.118, 2011.

J. Lawrence and . Hutchings, System and method for measuring movement of objects, US Patent, vol.5, p.265, 1998.

. Invensense and . Imu-mpu6050, , p.67

A. Jimenez-gonzalez, GAUSS: Galileo-EGNOS as an asset for UTM safety and security, vol.31, 2018.

W. Brett-johnson, S. Fatone, A. Steven, and . Gard, Walking mechanics of persons who use reciprocating gait orthoses, Journal of Rehabilitation Research & Development, vol.46, issue.3, 2009.

M. Johnson, B. Shrewsbury, S. Bertrand, D. Calvert, T. Wu et al., Team IHMC's lessons learned from the DARPA robotics challenge: finding data in the rubble, Journal of Field Robotics, vol.34, issue.2, p.52, 2017.

N. Kaempchen and K. Dietmayer, Data synchronization strategies for multi-sensor fusion, Proceedings of the IEEE Conference on Intelligent Transportation Systems, p.118, 2003.

M. Kaess, Incremental smoothing and mapping, vol.55, 2008.

M. Kaess, A. Ranganathan, and F. Dellaert, iSAM: Incremental smoothing and mapping, IEEE Transactions on Robotics, vol.24, issue.6, p.29, 2008.

M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. John et al., iSAM2: Incremental smoothing and mapping using the Bayes tree, The International Journal of Robotics Research, vol.31, issue.2, p.29, 2012.

R. E. and K. , A new approach to linear filtering and prediction problems, Journal of basic Engineering, vol.82, issue.1, pp.35-45, 1960.

N. Kanehira, S. Tu-kawasaki, . Ohta, T. Ismumi, F. Kawada et al., Design and experiments of advanced leg module (HRP-2L) for humanoid robot (HRP-2) development. In Intelligent Robots and Systems, vol.3, p.72, 2002.

K. Kaneko, M. Morisawa, S. Kajita, T. Shin'ichiro-nakaoka, R. Sakaguchi et al., Humanoid robot HRP-2Kai-Improvement of HRP-2 towards disaster response tasks, Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on, p.53, 2015.

S. Karumanchi, K. Edelberg, I. Baldwin, J. Nash, J. Reid et al., Team RoboSimian: semi-autonomous mobile manipulation at the 2015 DARPA robotics challenge finals, Journal of Field Robotics, vol.34, issue.2, pp.305-332, 2017.

H. Kawasaki, T. Komatsu, K. Uchiyama, and T. Kurimoto, Dexterous anthropomorphic robot hand with distributed tactile sensor: Gifu hand II, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on, vol.2, p.13, 1999.

O. Kerpa, K. Weiss, and H. Worn, Development of a flexible tactile sensor system for a humanoid robot, Proceedings. 2003 IEEE/RSJ International Conference on, vol.1, p.13, 2003.

D. Kim, S. Shin, and I. S. Kweon, On-Line Initialization and Extrinsic Calibration of an Inertial Navigation System With a Relative Preintegration Method on Manifold, IEEE Transactions on Automation Science and Engineering, vol.15, issue.3, 2018.

A. Lawrence, L. Klein, and . Klein, Sensor and data fusion: a tool for information assessment and decision making, vol.324, p.118, 2004.

M. Kok and N. Wahlström, Thomas B Schön and Fredrik Gustafsson. MEMS-based inertial navigation based on a magnetic field map, Acoustics, Speech and Signal Processing, pp.6466-6470, 2013.

M. Kok, D. Jeroen, . Hol, and . Thomas-b-schön, Indoor positioning using ultrawideband and inertial measurements, IEEE Transactions on Vehicular Technology, vol.64, issue.4, p.119, 2015.

D. Koller and N. Friedman, Probabilistic graphical models: principles and techniques, 2009.

K. Konolige, FrameSLAM: From bundle adjustment to real-time visual mapping, IEEE Transactions on Robotics, vol.24, issue.5, p.17, 2008.

M. Kourogi, T. Ishikawa, and T. Kurata, A method of pedestrian dead reckoning using action recognition, Position Location and Navigation Symposium (PLANS), pp.85-89, 2010.

A. Krasoulis, I. Kyranou, M. Suphi-erden, K. Nazarpour, and S. Vijayakumar, Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements, vol.14, p.71, 2017.

M. Kudruss, M. Naveau, O. Stasse, N. Mansard, and C. Kirches, Optimal control for whole-body motion generation using center-of-mass dynamics for predefined multi-contact configurations, Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on, p.116, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01179667

A. Rv-raja-kumar, R. C. Tirumalai, and . Jain, A nonlinear optimization algorithm for the estimation of structure and motion parameters, Proceedings CVPR'89., IEEE Computer Society Conference on, p.16, 1989.

R. Kümmerle, G. Grisetti, H. Strasdat, K. Konolige, and W. Burgard, g 2 o: A general framework for graph optimization, Robotics and Automation (ICRA), 2011 IEEE International Conference on, p.29, 2011.

, Surat Kwanmuang. FILTERING AND TRACKING FOR A PEDESTRIAN DEAD-RECKONING SYSTEM, 2015.

S. Bo-kyu-kwon and . Han, A robust extended Kalman filtering for linearization errors, Control, Automation and Systems (ICCAS), pp.1485-1487, 2015.

C. Lauretti, A. Davalli, R. Sacchetti, E. Guglielmelli, and L. Zollo, Fusion of M-IMU and EMG signals for the control of trans-humeral prostheses, Biomedical Robotics and Biomechatronics (BioRob), vol.125, pp.1123-1128, 2016.

T. Lenzi, L. Hargrove, and J. Sensinger, Speedadaptation mechanism: Robotic prostheses can actively regulate joint torque, IEEE Robotics & Automation Magazine, vol.21, issue.4, pp.94-107, 2014.

]. Leo, Techniques for nuclear and particle physics experiments, Nucl Instrum Methods Phys Res, vol.834, p.129, 1988.

S. Leutenegger, S. Lynen, M. Bosse, R. Siegwart, and P. Furgale, Keyframe-based visual-inertial odometry using nonlinear optimization, The International Journal of Robotics Research, vol.34, issue.3, p.38, 2015.

M. Li, H. Byung, A. Kim, and . Mourikis, Real-time motion tracking on a cellphone using inertial sensing and a rolling-shutter camera, Robotics and Automation (ICRA), 2013 IEEE International Conference on, pp.4712-4719, 2013.

Y. Liu, Z. Chen, W. Zheng, H. Wang, and J. Liu, Monocular Visual-Inertial SLAM: Continuous Preintegration and Reliable Initialization. Sensors, vol.17, p.2613, 2017.

H. Higgins, A computer algorithm for reconstructing a scene from two projections, Nature, vol.293, issue.5828, p.11, 1981.

I. A. Manolis and . Lourakis, A brief description of the Levenberg-Marquardt algorithm implemented by levmar, Foundation of Research and Technology, vol.4, issue.1, p.37, 2005.

A. Eugene and . Lovelace, Vision and kinesthesis in accuracy of hand movement, Perceptual and Motor Skills, vol.68, issue.3, pp.707-714, 1989.

F. Lu and E. Milios, Robot pose estimation in unknown environments by matching 2d range scans, Journal of Intelligent and Robotic systems, vol.18, issue.3, p.29, 1997.

T. Lupton and S. Sukkarieh, Efficient Integration of Inertial Observations into Visual SLAM without Initialization, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2009.

M. ]-Øyvind-magnussen, G. Ottestad, and . Hovland, Calibration procedure for an inertial measurement unit using a 6-degree-of-freedom hexapod, p.47, 2015.

P. Marion, M. Fallon, R. Deits, A. Valenzuela, C. Pérez-d'arpino et al., Director: A user interface designed for robot operation with shared autonomy, Journal of Field Robotics, vol.34, issue.2, pp.262-280, 2017.

W. Donald and . Marquardt, An algorithm for least-squares estimation of nonlinear parameters, Journal of the society for Industrial and Applied Mathematics, vol.11, issue.2, p.37, 1963.

A. Mifsud, ESTIMATING AND STABILIZING THE STATUS OF A COMBINING HUMANOID ROBOT. Theses, Institut national polytechnique de Toulouse (INPT), vol.79, 2017.
URL : https://hal.archives-ouvertes.fr/tel-01653163

M. Faraz, . Mirzaei, and . Stergios-i-roumeliotis, A Kalman filter-based algorithm for IMU-camera calibration: Observability analysis and performance evaluation, IEEE transactions on robotics, vol.24, issue.5, p.38, 2008.

M. Montemerlo, S. Thrun, and W. Whittaker, Conditional particle filters for simultaneous mobile robot localization and people-tracking, Proceedings. ICRA'02. IEEE International Conference on, vol.1, p.27, 2002.

M. Montemerlo and S. Thrun, FastSLAM 2.0. FastSLAM: A scalable method for the simultaneous localization and mapping problem in robotics, vol.27, p.17, 2007.

C. Juan, E. Moreno, . Rocon-de-lima, F. Andrés, . Ruíz et al., Design and implementation of an inertial measurement unit for control of artificial limbs: application on leg orthoses, Sensors and Actuators B: Chemical, vol.118, issue.1-2, pp.333-337, 2006.

E. Mouragnon, M. Lhuillier, M. Dhome, F. Dekeyser, and P. Sayd, Generic and real-time structure from motion using local bundle adjustment, Image and Vision Computing, vol.27, issue.8, p.17, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01635634

I. Anastasios, . Mourikis, and . Stergios-i-roumeliotis, A multi-state constraint Kalman filter for vision-aided inertial navigation, Robotics and automation, p.38, 2007.

N. Anastasios-i-mourikis, . Trawny, I. Stergios, A. E. Roumeliotis, A. Johnson et al., Vision-aided inertial navigation for spacecraft entry, descent, and landing, IEEE Transactions on Robotics, vol.25, issue.2, p.38, 2009.

J. Kyle, P. Mueller, M. Boyd, . Evans, E. Nance-ericson et al., A mobile motion analysis system using inertial sensors for analysis of lower limb prosthetics, Future of Instrumentation International Workshop, pp.59-62, 2011.

R. Robin and . Murphy, Dempster-Shafer theory for sensor fusion in autonomous mobile robots, IEEE Transactions on Robotics and Automation, vol.14, issue.2, p.118, 1998.

S. Shin'ichiro-nakaoka, F. Hattori, and . Kanehiro, Shuuji Kajita and Hirohisa Hirukawa. Constraint-based dynamics simulator for humanoid robots with shock absorbing mechanisms. In Intelligent Robots and Systems, IEEE/RSJ International Conference on, p.53, 2007.

, Out-of-core bundle adjustment for large-scale 3d reconstruction, Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, vol.17, pp.1-8, 2007.

, Multi-level submap based slam using nested dissection, Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, p.17, 2010.

J. Nilsson, K. Amit, P. Gupta, and . Händel, Foot-mounted inertial navigation made easy, Indoor Positioning and Indoor Navigation (IPIN), 2014 International Conference on, p.41, 2014.

J. Nilsson, I. Skog, and P. Händel, Aligning the forces-Eliminating the misalignments in IMU arrays, IEEE Transactions on Instrumentation and Measurement, vol.63, issue.10, p.48, 2014.

D. Novak and R. Riener, A survey of sensor fusion methods in wearable robotics, Robotics and Autonomous Systems, vol.73, p.119, 2015.

K. Ohno, T. Tsubouchi, B. Shigematsu, S. Maeyama, and . Shin'ichi-yuta, Outdoor navigation of a mobile robot between buildings based on DGPS and odometry data fusion, Proceedings. ICRA'03. IEEE International Conference on, vol.2, pp.1978-1984, 2003.

K. Ohno and T. Tsubouchi, Bunji Shigematsu and Shin'ichi Yuta. Differential GPS and odometry-based outdoor navigation of a mobile robot, Advanced Robotics, vol.18, issue.6, pp.611-635, 2004.

L. Ojeda and J. Borenstein, Personal dead-reckoning system for GPS-denied environments, Safety, Security and Rescue Robotics, pp.1-6, 2007.

J. Oliensis and . Thomas, Incorporating motion error in multiframe structure from motion, Proceedings of the IEEE Workshop on, p.16, 1991.

A. Ollero, AEROARMS: AErial RObotics System integrating multiple ARMS and advanced manipulation capabilities for inspection and maintenance, p.31, 2015.

B. Olofsson, J. Antonsson, G. Henk, B. Kortier, A. Bernhardsson et al., Sensor fusion for robotic workspace state estimation, IEEE/ASME Transactions on Mechatronics, vol.21, issue.5, p.119, 2016.

J. Olson, S. Leonard, and . Teller, Fast iterative alignment of pose graphs with poor initial estimates, Proceedings 2006 IEEE International Conference on, p.29, 2006.

B. Edwin and . Olson, Robust and efficient robotic mapping, p.28, 2008.

F. Olsson, M. Kok, K. Halvorsen, and . Thomas-b-schön, Accelerometer calibration using sensor fusion with a gyroscope, Bibliography Statistical Signal Processing Workshop (SSP), p.118, 2016.

G. Panahandeh, N. Mohammadiha, A. Leijon, and P. Händel, Chest-mounted inertial measurement unit for pedestrian motion classification using continuous hidden Markov model, Instrumentation and Measurement Technology Conference (i2mtc), 2012 IEEE International, p.65, 2012.

H. Park, M. Patrick, S. Wensing, and . Kim, Online planning for autonomous running jumps over obstacles in high-speed quadrupeds, 2015.

E. Mark and . Pittelkau, Cascaded and decoupled RIMU calibration filters, The Journal of the Astronautical Sciences, vol.54, issue.3-4, pp.449-466, 2006.

F. Pomerleau, F. Colas, R. Siegwart, and S. Magnenat, Comparing ICP variants on real-world data sets, Autonomous Robots, vol.34, issue.3, p.53, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01143458

M. Garcia-puyol, P. Robertson, and O. Heirich, Complexity-reduced FootSLAM for indoor pedestrian navigation, Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on, p.66, 2012.

A. ]-giulio-reina, K. Vargas, K. Nagatani, and . Yoshida, Adaptive kalman filtering for gps-based mobile robot localization, SSRR 2007. IEEE International Workshop on, vol.3, pp.1-6, 2007.

N. Rotella, S. Mason, S. Schaal, and L. Righetti, Inertial sensor-based humanoid joint state estimation, Robotics and Automation (ICRA), 2016 IEEE International Conference on, pp.1825-1831, 2016.

C. Roussillon, A. Gonzalez, J. Solà, J. Codol, N. Mansard et al., RT-SLAM: a generic and real-time visual SLAM implementation, International Conference on Computer Vision Systems, pp.31-40, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00662647

A. Ruiz, F. Seco-granja, J. Honorato, and J. Rosas, Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements, IEEE Transactions on Instrumentation and Measurement, vol.61, issue.1, p.66, 2012.

A. Santamaria-navarro, P. Grosch, V. Lippiello, J. Solà, and J. Andrade-cetto, Uncalibrated visual servo for unmanned aerial manipulation, IEEE/ASME Transactions on Mechatronics, vol.22, issue.4, pp.1610-1621, 2017.

A. Santamaria-navarro, G. Loianno, J. Solà, V. Kumar, and J. Andrade-cetto, Autonomous navigation of micro aerial vehicles using high-rate and low-cost sensors, Autonomous Robots, pp.1-18, 2017.

F. Santoso, A. Matthew, . Garratt, G. Sreenatha, and . Anavatti, Visual-inertial navigation systems for aerial robotics: Sensor fusion and technology, IEEE Transactions on Automation Science and Engineering, vol.14, issue.1, p.119, 2017.

T. Schauer, . Seel, P. Bunt, J. C. Müller, and . Moreno, Realtime EMG analysis for transcutaneous electrical stimulation assisted gait training in stroke patients, IFAC-PapersOnLine, vol.49, issue.32, pp.183-187, 2016.

D. Schulz, W. Burgard, D. Fox, B. Armin, and . Cremers, Tracking multiple moving targets with a mobile robot using particle filters and statistical data association, ICRA. IEEE International Conference on, vol.2, p.27, 2001.

T. Seel, J. Raisch, and T. Schauer, IMU-based joint angle measurement for gait analysis, Sensors, vol.14, issue.4, pp.6891-6909, 2014.

, Learning control and inertial realtime gait analysis in biomedical applications, vol.125, 2016.

T. Seel, C. Werner, J. Raisch, and T. Schauer, Iterative learning control of a drop foot neuroprosthesis-Generating physiological foot motion in paretic gait by automatic feedback control, Control Engineering Practice, vol.48, pp.87-97, 2016.

H. Shum, Q. Ke, and Z. Zhang, Efficient bundle adjustment with virtual key frames: A hierarchical approach to multi-frame structure from motion, Computer Vision and Pattern Recognition, vol.2, p.17, 1999.

R. Siegwart, Illah Reza Nourbakhsh and Davide Scaramuzza, 2011.

R. Sim, P. Elinas, M. Griffin, J. James, and . Little, Visionbased SLAM using the Rao-Blackwellised particle filter, IJCAI Workshop on Reasoning with Uncertainty in Robotics, vol.14, pp.9-16, 2005.

I. Skog and P. Händel, Calibration of a MEMS inertial measurement unit, XVII IMEKO world congress, p.47, 2006.

I. Skog, J. Nilsson, D. Zachariah, and P. Händel, Fusing the information from two navigation systems using an upper bound on their maximum spatial separation, Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on, p.66, 2012.

S. ?lajpah, R. Kamnik, and M. Munih, Kinematics based sensory fusion for wearable motion assessment in human walking, Computer methods and programs in biomedicine, vol.116, issue.2, pp.131-144, 2014.

S. Soatto, P. Perona, R. Frezza, and G. Picci, Recursive motion and structure estimation with complete error characterization, Computer Vision and Pattern Recognition, 1993. Proceedings CVPR'93, p.16, 1993.

J. Ortega, Quaternion kinematics for the error-state KF, p.131, 2016.

, Towards visual localization, mapping and moving objects tracking by a mobile robot: a geometric and probabilistic approach, 2007.

]. Sola, Course on SLAM. Institut de Robotica i Informatica Industrial (IRI), 2016.

J. Solà, J. Deray, and D. Atchuthan, A micro Lie theory for state estimation in robotics, 2018.

P. Demetri, R. Spanos, -. Olfati, R. Saber, and . Murray, Distributed sensor fusion using dynamic consensus, IFAC World Congress. Citeseer, p.118, 2005.

M. Spetsakis and J. Yiannis-aloimonos, A multi-frame approach to visual motion perception, International Journal of Computer Vision, vol.6, issue.3, p.16, 1991.

, Stachniss 2013] Cyrill Stachniss. Robot Mapping, vol.17, p.11, 2013.

A. J. Olivier-stasse, R. Davison, K. Sellaouti, and . Yokoi, Real-time 3d slam for humanoid robot considering pattern generator information, Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, p.53, 2006.

O. Stasse, T. Flayols, R. Budhiraja, K. Giraud-esclasse, J. Carpentier et al., Andrea Del Prete, Philippe Souères, Nicolas Mansard, Florent Lamirauxet al. TALOS: A new humanoid research platform targeted for industrial applications, Humanoid Robotics (Humanoids), 2017 IEEE-RAS 17th International Conference on, p.117, 2017.

D. Steedly and I. Essa, Propagation of innovative information in non-linear least-squares structure from motion, Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, vol.2, p.17, 2001.

D. Steins, I. Sheret, H. Dawes, P. Esser, and J. Collett, A smart device inertial-sensing method for gait analysis, Journal of biomechanics, vol.47, issue.15, pp.3780-3785, 2014.

V. James and . Stone, Bayes' rule: A tutorial introduction to bayesian analysis, p.129, 2013.

H. Strasdat, J. Montiel, and A. Davison, Real-time monocular SLAM: Why filter?, Robotics and Automation (ICRA), 2010.

, IEEE International Conference on, pp.2657-2664, 2010.

H. Strasdat, M. M. José, A. Montiel, and . Davison, Visual SLAM: why filter? Image and Vision Computing, vol.30, p.17, 2012.

R. Szeliski, B. Sing, and . Kang, Recovering 3D shape and motion from image streams using nonlinear least squares, Journal of Visual Communication and Image Representation, vol.5, issue.1, p.17, 1994.

D. Tedaldi, IMU calibration without mechanical equipment.(Calibrazione di IMU svincolata da apparati meccanici), 2013.

S. Thrun, W. Burgard, and D. Fox, Probabilistic robotics, 2005.

S. Thrun and M. Montemerlo, The graph SLAM algorithm with applications to large-scale mapping of urban structures, The International Journal of Robotics Research, vol.25, issue.5-6, p.29, 2006.

D. Titterton, L. John, J. Weston, and . Weston, Strapdown inertial navigation technology, IET, vol.17, p.43, 2004.

. Philip-f-mclauchlan, I. Richard, A. W. Hartley, and . Fitzgibbon, Bundle adjustment-a modern synthesis, International workshop on vision algorithms, p.16, 1999.

P. Dimitris, P. Tsakiris, C. Rives, and . Samson, Applying visual servoing techniques to control nonholonomic mobile robots, International Conference on Intelligent Robots and Systems, 1997.

J. Vallvé and J. Andrade-cetto, Active pose SLAM with RRT, Robotics and Automation (ICRA), 2015 IEEE International Conference on, vol.120, pp.2167-2173, 2015.

J. Vallvé, J. Solà, and J. Andrade-cetto, Factor descent optimization for sparsification in graph SLAM, Mobile Robots (ECMR, p.2017

, European Conference on, vol.120, pp.1-6, 2017.

J. Vallvé, J. Solà, and J. Andrade-cetto, Graph SLAM sparsification with populated topologies using factor descent optimization, IEEE Robotics and Automation Letters, vol.3, issue.2, pp.1322-1329, 2018.

A. C. Victorino, P. Rives, and J. Borrelly, Safe navigation for indoor mobile robots. Part I: a sensor-based navigation framework, The International Journal of Robotics Research, vol.22, issue.12, p.116, 2003.
URL : https://hal.archives-ouvertes.fr/inria-00327593

B. Wagstaff, V. Peretroukhin, and J. Kelly, Improving Foot-Mounted Inertial Navigation Through Real-Time Motion Classification, 2017.

A. Eric, R. Wan, and . Van-der-merwe, The unscented Kalman filter for nonlinear estimation, Adaptive Systems for Signal Processing, Communications, and Control Symposium, pp.153-158, 2000.

J. Weng, N. Ahuja, S. Thomas, and . Huang, Optimal motion and structure estimation, IEEE Transactions, vol.15, issue.9, p.16, 1993.

G. Olive and . Young, A study of kinesthesis in relation to selected movements. Research Quarterly. American Association for Health, Physical Education and Recreation, vol.16, issue.4, pp.277-287, 1945.

H. Zhao, J. Horn, J. Reher, V. Paredes, and A. Ames, Multicontact locomotion on transfemoral prostheses via hybrid system models and optimization-based control, IEEE Transactions on Automation Science and Engineering, vol.13, issue.2, pp.502-513, 2016.