Underwater images are altered by the physical characteristics of the medium through which light rays pass before reaching the optical sensor. Scattering and wavelength-dependent absorption significantly modify the captured colors depending on the distance of observed elements to the image plane. In this paper, we aim to recover an image of the scene as if the water had no effect on light propagation. We introduce SUCRe, a novel method that exploits the scene’s 3D structure for underwater color restoration. By following points in multiple images and tracking their intensities at different distances to the sensor, we constrain the optimization of the parameters in an underwater image formation model and retrieve unattenuated pixel intensities. We conduct extensive quantitative and qualitative analyses of our approach in a variety of scenarios ranging from natural light to deep-sea environments using three underwater datasets acquired from real-world scenarios and one synthetic dataset. We also compare the performance of the proposed approach with that of a wide range of existing state-of-the-art methods. The results demonstrate a consistent benefit of exploiting multiple views across a spectrum of objective metrics. Our code is publicly available at github.com/clementinboittiaux/sucre.

This paper examines the relevance of using catenary-based curves to model cables in underwater tethered robotic applications in order to take into account the influence of hydrodynamic damping. To this end, an augmented catenary-based model is introduced to deal with the dynamical effects of surge motion, sway motion or a combination of both on a cable. Experimental studies are carried out with eight cables of varying stiffness, weight and buoyancy. One end of the cable is fixed, while the other end is moved by the underwater robot. The obtained results help to determine which cables and which dynamics are compatible with a fair estimation of the cable shape through the proposed models.

This study is twofold. First, a comprehensive simulation framework of cable dynamics is introduced. This framework considers variable length cables and allows to incorporate elements such as buoys, ballast or Inertial Measurement Unit (IMU) sensors. The accuracy of this framework is assessed through experimental data. Second, a novel and improved solution for the instrumentation of a V-shaped buoy-ballast system using IMU sensors is investigated. This latter, designed for a neutrally buoyant tether between a Remotely Operated Vehicle (ROV) and an Unmanned Surface Vehicle (USV), is meant to improve operation safety. The discussed IMU-based solution provides wider information on the interaction between the ROV and the cable, including its 3D orientation and curvature amplitude, which could be used for both the control of the USV trajectory and its onboard winch.

This paper deals with the estimation of the shape of a catenary for a negatively buoyant cable, connecting a pair of underwater robots in a robot chain. The new estimation method proposed here is based on the calculation of local tangents thanks to the data acquired from inertial measurement units (IMUs), which are attached to the cable near its ends. This method is compared with a vision-based estimation method that was developed previously. Experiments are conducted, in the air and in a pool, using a motion capture system for ground truth. The results obtained show that the new method significantly improves the estimation of the catenary height. Furthermore, the identification of the cable shape is not affected by the limits of the camera's field of view and by the image projection, resulting in increased accuracy and range, without singularities.

This paper focuses on numerical methods that can be used to identify hydrodynamic parameters of submerged bodies, namely added mass, linear and quadratic friction coefficients. The mechanical setup is a free decay pendulum that is equipped with an encoder. The first contribution of this paper deals with the comparison of two estimation methods: one method that fits the acceleration of the dynamical model with the acceleration obtained from derivatives of the measured angular position, and another method that fits this position with the angle obtained by numerical integration. The second contribution consists of investigating to what extent estimated added mass and friction coefficient parameters of the dynamical model match the empirical or theoretical values in the case of a spherical object. The results obtained show that the numerical integration method allows to determine the added mass with a good accuracy and a single friction coefficient could be used for the dynamic model without loosing validity.

Tethers are used to supply power and transfer data for teleoperated robots. They are known to limit the robot's workspace and could have the effect of hampering its motion. What if we could take advantage of the tether? In this paper a new visual servoing scheme for catenary shaped deformable objects is introduced in order to control the tether parametric shape by properly moving its fixation point. In most of the visual servoing approaches the target object is rigid and distant from the controlled robot. On the contrary, in this paper, the object is deformable and attached to the robot, thus its 3D shape changes while the robot is moving. The experimental system is composed of two terrestrial mobile robots of the same motion capabilities linked with a slack rope. Simulation and real experiments validate the proposed control scheme for proper tether handling.

We present here a simple technique of inverse kinematics to be used for humanoid legs. This technique has two advantages. First it permits to manage the stretched-legs space boundary singularities encountered with the classical inverse kinematics that uses a whole Jacobian matrix for all leg joint angle variations. This leg singularity configuration always appears when the humanoid robot has to get from the standing position with both legs stretched to a knee flexed position and vice-versa. Second the technique is independent of the convention of angle orientation at the hips and at the ankles. Therefore it does not require the specific solving for hip and ankle joint angles of the rotation matrix equations in the case of analytical geometric methods. The inverse kinematics proposed here is based on geometrical calculations to get knee coordinates, and on the decomposition of inverse leg kinematics, i.e. inverse kinematics at the hip for the one part, and inverse kinematics at the ankle for the other part. This calculation assumes that the leg has six rotary degrees of freedom, three at the hip, one at the knee, and two at the ankle. The orientation of rotary joints at the hip and at the ankle can be arbitrary.

In the human brain, rewards are encoded in a flexible and adaptive way after each novel stimulus. Neurons of the orbitofrontal cortex are the key reward structure of the brain. Neurobiological studies show that the anterior cingulate cortex of the brain is primarily responsible for avoiding repeated mistakes. According to vigilance threshold, which denotes the tolerance to risks, we can differentiate between a learning mechanism that takes risks and one that averts risks. The tolerance to risk plays an important role in such a learning mechanism. Results have shown the differences in learning capacity between risk-taking and risk-avert behaviors. These neurological properties provide promising inspirations for robot learning based on rewards. In this paper, we propose a learning mechanism that is able to learn from negative and positive feedback with reward coding adaptively. It is composed of two phases: evaluation and decision making. In the evaluation phase, we use a Kohonen self-organizing map technique to represent success and failure. Decision making is based on an early warning mechanism that enables avoiding repeating past mistakes. The behavior to risk is modulated in order to gain experiences for success and for failure. Success map is learned with adaptive reward that qualifies the learned task in order to optimize the efficiency. Our approach is presented with an implementation on the NAO humanoid robot, controlled by a bioinspired neural controller based on a central pattern generator. The learning system adapts the oscillation frequency and the motor neuron gain in pitch and roll in order to walk on flat and sloped terrain, and to switch between them.

Taking into consideration the architecture of the human spine, we propose the construction of a module whose series could be used as a robotic spine*. This module is basically constituted by an elastic diabolo, which mimics the vertebral bodies and the intervertebral disc, joining two metallic setsquares - the two consecutive vertebrae. Two actuators realize the actuation of the module and are oriented parallel to the main axis of the diabolo. This simple compliant model allowed us to construct a demonstrator that will be used to measure the incidence of active and passive movements of the model. From the knowledge of these results we will design a new compliant system in place of the elastic diabolo whose characteristics will be adequate to the convenient properties of the spine that could be included in humanoid machines.

We present here a detailed description of the walking algorithm that was designed for 3D simulation of locomotion and path planning of humanoid robots. The walking patterns described were implemented on NAO humanoid models that are used in the 3D simulation league of RoboCup to play soccer. The locomotion algorithm is based on the well known 3D-LIP model that consists of defining walking primitives of the center of mass, keeping its height constant and assuming no torque at the support foot. This paper proposes to detail how to connect the walking primitives, especially at the start of the walk. The second added value of this work resides in the rotation walking primitives that are generated differently from the linear translation walking primitives. This enables the robot to achieve fast rotation on the spot or about a center located on the longitudinal axis. The paper also addresses the issue of re-entrance, i.e. how to take into account a new walking request in real time without waiting for the end of the current walk.

We present the design of a bird-like kinematics model for a biped robot as an alternative to the human model. The starting point of the research consists of analyzing the walking motion of quail birds using biological data obtained by X-ray radiography. The 3-D-motion analysis allows identification of the number of degrees of freedom (DOF) and the rotation mechanism for each leg, especially the main rotation axis. Leg joints are located at the hip, knee, ankle, and foot. The ankle is off the ground. Using this analysis, we have designed a biped kinematics model with a minimum of actuated joints and with the original orientation of hip and ankle main rotary joints, which are not horizontally and vertically oriented as in classical biped robotics. Given a reference-foot trajectory, we carry out simulations to compare internal-joint trajectories with the ones obtained from biological measurements. We show that the proposed model can be used to reproduce the kinematics of bird locomotion with a minimum of four actuated joints per leg, i.e., two at the hip and one at the knee, and one at the ankle, which is less than the usual six joints per leg that drive anthropomorphic legs.

This article presents the mechatronic design of the autonomous humanoid robot called NAO that is built by the French company Aldebaran-Robotics. With its height of 0.57 m and its weight about 4.5 kg, this innovative robot is lightweight and compact. It distinguishes itself from existing humanoids thanks to its pelvis kinematics design, its proprietary actuation system based on brush DC motors, its electronic, computer and distributed software architectures. This robot has been designed to be affordable without sacrificing quality and performance. It is an open and easy-to-handle platform. The comprehensive and functional design is one of the reasons that helped select NAO to replace the AIBO quadrupeds in the 2008 RoboCup standard league.

Pivoting manipulation can be an alternative to pushing operation when the floor is not flat enough, or when the object to manipulate is too heavy. The technique of pivoting is used by humans to move large and bulky furniture from one place to another. The decomposition of the task of pivoting has already been studied, in particular with the use of two fingers of a robotic arm. This work intends to apply the technique of pivoting using an humanoid platform. The robot should be able to pivot the object and to walk with it to displace it to a specific remote location. The research achievements proposed here take place in a more long term objective aimed at improving the dexterity and the autonomy of humanoid robots. As a matter of fact, such robots should be able to handle objects and move around in the environment in an autonomous way. This paper describes the algorithm designed to perform the displacement of a large object using the pivoting technique. It also presents the results of the dynamic simulation and the results of the real hardware experiment of the HRP-2 platform performing the task.

To operate in a known and dynamic environment, a robot needs two different kinds of a priori knowledge : behavioral and visual. In this paper we propose a general methodology to introduce this a priori knowledge, and we illustrate it by an application : the software developments for the AIBO robots to play soccer. The more difficult task is to extract reliable visual information. It is the reason why a priori knowledge is already introduced at the level of vision processing. Without reliable vision information it is impossible for the robot to switch to the tight behavior, and consequently to play.

This work deals with the design of a locomotion algorithm that changes the speed of a crawling quadruped by varying the duty factor /spl beta/. The walking pattern used is the well-known wave gait. This kind of gait should be maintained as much as possible since it is the most efficient locomotion pattern on flat ground. However, the transition between initial and final gaits cannot be based on a wave gait any more because support legs have to be resynchronized according to a new duty factor. This paper proposes an algorithm that deals with the gait transition between initial and final duty factors.

This paper deals with the description of the strategy adopted by the French team in the Sony legged league to play soccer. Not only the behaviors designed for RoboCup are presented, but also the arrangement of the three different modules inside the robot, namely the vision, locomotion and strategy modules. The vision module runs at lower priority and provides others with relevant information captured from the environment. The locomotion module is responsible for the walking gaits generation. It manages transitions between forward, turning and rotation modes. It incorporates changes in speed, and recovery procedures in case the robot falls down. The paper focuses on how the decision or other behaviors are being taken. The overall architecture and the communications between the three modules are also described.

Deals with the implementation of an efficient walking pattern for quadruped robots. The main objective is to give the robot the ability to walk in every direction as quickly as possible. Not only forward motion, but also backward motion, turning gaits of variable curvature including rotation around the body platform center of gravity (COG) are considered separately. For this purpose the well known crawl gait with duty factor of 3/4 represents the starting point of the experimental study. From this point the regular symmetric gait is improved thanks to sideways motion, turning gaits are adapted from the forward crawl gait and a special rotation motion is designed. All transitions between forward, backward, left and right turning and rotation motions are detailed. Experiments have been carried out using the Sony quadruped "pet robot" prototype which look part in the Paris Robocup-98 legged robot exhibition.

This paper focuses on the description and the performance analysis of a new type of force feedback handle with special features. This handle has the shape of a cylindrical stick whose upper part can move with respect to the lower part. The operator seizes both parts of this handle with his hand and can move around in the surrounding space, feeling reaction forces from the upper part. This manipulator has been integrated within a global control station. The experimental layout is provided with virtual environment generation which manages the interaction of the handle with the real world. The experiments we conducted have shown interesting results.