RAINBOW: robotique interactive et référencée capteurs

In this letter, we address the problem of extracting a feasible set of dynamic parameters characterizing the dynamics of a robot manipulator. We start by identifying through an ordinary least squares approach the dynamic coefficients that linearly parametrize the model. From these, we retrieve a set of feasible link parameters (mass, position of center of mass, inertia) that is fundamental for more realistic dynamic simulations or when implementing in real time robot control laws using recursive NewtonEuler algorithms. The resulting problem is solved by means of an optimization method that incorporates constraints on the physical consistency of the dynamic parameters, including the triangle inequality of the link inertia tensors as well as other user-defined, possibly nonlinear constraints. The approach is developed for the increasingly popular Panda robot by Franka Emika, identifying for the first time its dynamic coefficients, an accurate joint friction model, and a set of feasible dynamic parameters. Validation of the identified dynamic model and of the retrieved feasible parameters is presented for the inverse dynamics problem using, respectively, a Lagrangian approach and Newton-Euler computations.

We present a contact planner for complex legged locomotion tasks: standing up, climbing stairs using a handrail, crossing rubble, and getting out of a car. The need for such a planner was shown at the DARPA Robotics Challenge, where such behaviors could not be demonstrated (except for egress). Current planners suffer from their prohibitive algorithmic complexity because they deploy a tree of robot configurations projected in contact with the environment. We tackle this issue by introducing a reduction property: the reachability condition. This condition defines a geometric approximation of the contact manifold, which is of low dimension, presents a Cartesian topology, and can be efficiently sampled and explored. The hard contact planning problem can then be decomposed into two subproblems: first, we plan a path for the root without considering the whole-body configuration, using a sampling-based algorithm; then, we generate a discrete sequence of whole-body configurations in static equilibrium along this path, using a deterministic contact-selection algorithm. The reduction breaks the algorithm complexity encountered in previous works, resulting in the first interactive implementation of a contact planner (open source). While no contact planner has yet been proposed with theoretical completeness, we empirically show the interest of our framework: in a few seconds, with high success rates, we generate complex contact plans for various scenarios and two robots: HRP-2 and HyQ. These plans are validated in dynamic simulations or on the real HRP-2 robot.

This paper presents an adaptive trajectory tracking control strategy for quadrotor micro aerial vehicles (MAVs). The proposed approach, while maintaining the common assumption of an orientation dynamics faster than the translational one, removes the assumption of absence of external disturbances and of geometric center coincident with the Center of Mass (CoM). In particular, the trajectory tracking control law is made adaptive with respect to the presence of external forces and moments (e.g., due to wind) and to the uncertainty of parameters of the dynamic model, such as the position of the CoM. A stability analysis is presented to analytically support the proposed controller, while numerical simulations are provided in order to validate its performance.

In this letter, we investigate the online generation of optimal trajectories for target tracking with a quadrotor while satisfying a set of image-based and actuation constraints. We consider a quadrotor equipped with a camera (either down or front-looking) with limited field of view. The aim is to follow in a smooth but reactive way a moving target while avoiding obstacles in the environment and occlusions in the image space. We propose vision-based approaches based on multiobjective optimization, especially with the occlusion constraint formulation. We design an online replanning strategy inspired from model predictive control that successively solves a nonlinear optimization problem. The problem is formulated as a nonlinear program (NLP) using differential flatness and finite parametrization with B-Splines. This allows a resolution by sequential quadratic programming (SQP) at a rate of 30 Hz. The robustness and reactivity of the replanning algorithm are demonstrated through realistic simulation results. Experiments validating the performance with a real quadrotor are also presented.

Tangible objects are used in virtual reality (VR) and augmented reality (AR) to enhance haptic information on the general shape of virtual objects. However, they are often passive or unable to simulate rich varying mechanical properties. This article studies the effect of combining simple passive tangible objects and wearable haptics for improving the display of varying stiffness, friction, and shape sensations in these environments. By providing timely cutaneous stimuli through a wearable finger device, we can make an object feel softer or more slippery than it really is, and we can also create the illusion of encountering virtual bumps and holes. We evaluate the proposed approach carrying out three experiments with human subjects. Results confirm that we can increase the compliance of a tangible object by varying the pressure applied through a wearable device. We are also able to simulate the presence of bumps and holes by providing timely pressure and skin stretch sensations. Altering the friction of a tangible surface showed recognition rates above the chance level, albeit lower than those registered in the other experiments. Finally, we show the potential of our techniques in an immersive medical palpation use case in VR. These results pave the way for novel and promising haptic interactions in VR, better exploiting the multiple ways of providing simple, unobtrusive, and inexpensive haptic displays.

This letter presents a wearable haptic device for the forearm and its application in robotic teleoperation. The device is able to provide skin stretch, pressure, and vibrotactile stimuli. Two servo motors, housed in a 3D printed lightweight platform, actuate an elastic fabric belt, wrapped around the arm. When the two servo motors rotate in opposite directions, the belt is tightened (or loosened), thereby compressing (or decompressing) the arm. On the other hand, when the two motors rotate in the same direction, the belt applies a shear force to the arm skin. Moreover, the belt houses four vibrotactile motors, positioned evenly around the arm at 90° from each other. The device weights 220 g for 115 × 122 × 50 mm of dimensions, making it wearable and unobtrusive. We carried out a perceptual characterization of the device as well as two human-subjects teleoperation experiments in a virtual environment, employing a total of 34 subjects. In the first experiment, participants were asked to control the motion of a robotic manipulator for grasping an object; in the second experiment, participants were asked to teleoperate the motion of a quadrotor fleet along a given path. In both scenarios, the wearable haptic device provided feedback information about the status of the slave robot(s) and of the given task. Results showed the effectiveness of the proposed device. Performance on completion time, length trajectory, and perceived effectiveness when using the wearable device improved of 19.8%, 25.1%, and 149.1% than when wearing no device, respectively. Finally, all subjects but three preferred the conditions including wearable haptics.

This paper introduces DREGON, a novel publicly-available dataset that aims at pushing research in sound source localization using a microphone array embedded in an unmanned aerial vehicle (UAV). The dataset contains both clean and noisy in-flight audio recordings continuously annotated with the 3D position of the target sound source using an accurate motion capture system. In addition, various signals of interests are available such as the rotational speed of individual rotors and inertial measurements at all time. Besides introducing the dataset, this paper sheds light on the specific properties, challenges and opportunities brought by the emerging task of UAV-embedded sound source localization. Several baseline methods are evaluated and compared on the dataset, with real-time applicability in mind. Very promising results are obtained for the localization of a broad-band source in loud noise conditions, while speech localization remains a challenge under extreme noise levels.

We present a novel three Revolute-Revolute-Spherical (3RRS) wearable fingertip device for the rendering of stiffness information. It is composed of a static upper body and a mobile end-effector. The upper body is located on the nail side of the finger, supporting three small servo motors, and the mobile end-effector is in contact with the finger pulp. The two parts are connected by three articulated legs, actuated by the motors. The end-effector can move toward the user's fingertip and rotate it to simulate contacts with arbitrarily-oriented surfaces. Moreover, a vibrotactile motor placed below the end-effector conveys vibrations to the fingertip. The proposed device weights 25 g for 35 x 50 x 48 mm dimensions. To test the effectiveness of our wearable haptic device and its level of wearability, we carried out two experiments, enrolling 30 human subjects in total. The first experiment tested the capability of our device in differentiating stiffness information, while the second one focused on evaluating its applicability in an immersive virtual reality scenario. Results showed the effectiveness of the proposed wearable solution, with a JND for stiffness of 208.5 17.2 N/m. Moreover, all subjects preferred the virtual interaction experience when provided with wearable cutaneous feedback, even if results also showed that subjects found our device still a bit difficult to use.

In this paper, we present a novel modular wearable interface for haptic interaction and robotic teleoperation. It is composed of a 3-degree-of-freedom (3-DoF) fingertip cutaneous device and a 1-DoF finger kinesthetic exoskeleton, which can be either used together as a single device or separately as two different devices. The 3-DoF fingertip device is composed of a static body and a mobile platform. The mobile platform is capable of making and breaking contact with the finger pulp and reangle to replicate contacts with arbitrarily oriented surfaces. The 1-DoF finger exoskeleton provides kinesthetic force to the proximal and distal interphalangeal finger articulations using one servo motor grounded on the proximal phalanx. This paper presents the wearable device as well as three different position, force, and compliance control schemes, together with their evaluations. We also present three human subjects experiments, enrolling a total of 40 different participants: the first experiment considered a curvature discrimination task, the second one a robot-assisted palpation task, and the third one an immersive experience in virtual reality. Results show that providing cutaneous and kinesthetic feedback through our device significantly improve the performance of all the considered tasks. Moreover, although cutaneous-only feedback shows promising performance, adding kinesthetic feedback improves most metrics. Finally, subjects rank our device as highly wearable, comfortable, and effective.

Abstract The real‐time simulation of human crowds has many applications. Simulating how the people in a crowd move through an environment is an active and ever‐growing research topic. Most research focuses on microscopic (or ‘agent‐based’) crowd‐simulation methods that model the behavior of each individual person, from which collective behavior can then emerge. This state‐of‐the‐art report analyzes how the research on microscopic crowd simulation has advanced since the year 2010. We focus on the most popular research area within the microscopic paradigm, which is local navigation, and most notably collision avoidance between agents. We discuss the four most popular categories of algorithms in this area (force‐based, velocity‐based, vision‐based, and data‐driven) that have either emerged or grown in the last decade. We also analyze the conceptual and computational (dis)advantages of each category. Next, we extend the discussion to other types of behavior or navigation (such as group behavior and the combination with path planning), and we review work on evaluating the quality of simulations. Based on the observed advancements in the 2010s, we conclude by predicting how the research area of microscopic crowd simulation will evolve in the future. Overall, we expect a significant growth in the area of data‐driven and learning‐based agent navigation, and we expect an increasing number of methods that re‐group multiple ‘levels’ of behavior into one principle. Furthermore, we observe a clear need for new ways to analyze (real or simulated) crowd behavior, which is important for quantifying the realism of a simulation and for choosing the right algorithms at the right time.

This article proposes a shared-control teleoperation architecture for robot manipulators transporting an object on a tray. Differently from many existing studies about remotely operated robots with firm grasping capabilities, we consider the case in which, in principle, the object can break its contact with the robot end-effector. The proposed shared-control approach automatically regulates the remote robot motion commanded by the user and the end-effector orientation to prevent the object from sliding over the tray. Furthermore, the human operator is provided with haptic cues informing about the discrepancy between the commanded and executed robot motion, which assist the operator throughout the task execution. We carried out trajectory tracking experiments employing an autonomous 7-degree-of-freedom (DoF) manipulator and compared the results obtained using the proposed approach with two different control schemes (i.e., constant tray orientation and no motion adjustment). We also carried out a human-subjects study involving 18 participants in which a 3-DoF haptic device was used to teleoperate the robot linear motion and display haptic cues to the operator. In all experiments, the results clearly show that our control approach outperforms the other solutions in terms of sliding prevention, robustness, commands tracking, and user’s preference.

Encountered-Type Haptic Displays (ETHDs) provide haptic feedback by positioning a tangible surface for the user to encounter. This permits users to freely eliciting haptic feedback with a surface during a virtual simulation. ETHDs differ from most of current haptic devices which rely on an actuator always in contact with the user. This article intends to describe and analyze the different research efforts carried out in this field. In addition, this article analyzes ETHD literature concerning definitions, history, hardware, haptic perception processes involved, interactions and applications. The paper proposes a formal definition of ETHDs, a taxonomy for classifying hardware types, and an analysis of haptic feedback used in literature. Taken together the overview of this survey intends to encourage future work in the ETHD field.

Haptic shared control enables a human operator and an autonomous controller to share the control of a robotic system using haptic active constraints. It has been used in robotic teleoperation for different purposes, such as navigating along paths minimizing the torques requested to the manipulator or avoiding possibly dangerous areas of the workspace. However, few works have focused on using these ideas to account for the user's comfort. In this article, we present an innovative haptic-enabled shared control approach aimed at minimizing the user's workload during a teleoperated manipulation task. Using an inverse kinematic model of the human arm and the rapid upper limb assessment (RULA) metric, the proposed approach estimates the current user's comfort online. From this measure and an a priori knowledge of the task, we then generate dynamic active constraints guiding the users towards a successful completion of the task, along directions that improve their posture and increase their comfort. Studies with human subjects show the effectiveness of the proposed approach, yielding a 30% perceived reduction of the workload with respect to using standard guided human-in-the-loop teleoperation.

In cable-driven parallel robots (CDPRs), rigid links are substituted by flexible cables. This change in actuation allows for a large workspace with a high payload to weight ratio, among other appealing characteristics. However, the accuracy for such systems needs to be improved to truly outperform classical parallel robots. A possible and not yet well studied solution is the use of vision-based control for CDPRs. This letter deals with the stability analysis of such a control scheme with regard to uncertainties lying both in the analytical models and the experimental setup. Two CDPRs are analyzed as illustrative examples. The results obtained show the system's robustness with respect to uncertainties.

Navigating in virtual environments requires using some locomotion interfaces, especially when the dimensions of the environment exceed the ones of the Virtual Reality system. Locomotion interfaces induce some biases both in the perception of the self-motion or in the formation of virtual locomotion trajectories. These biases have been mostly evaluated in the context of static environments, and studies need to be revisited in the new context of populated environments where users interact with virtual characters. We focus on a situation of collision avoidance between a real participant and a virtual character, and compared it to previous studies on real walkers. Our results show that, as in reality, the risk of future collision is accurately anticipated by participants, however with delay. We also show that collision avoidance trajectories formed in VR have common properties with real ones, with some quantitative differences in avoidance distances. More generally, our evaluation demonstrates that reliable results can be obtained for qualitative analysis of small scale interactions in VR. We discuss these results in the perspective of a VR platform for large scale interaction applications, such as in a crowd, for which real data are difficult to gather.

People with severe disabilities often rely on power wheelchairs for moving around. However, if their driving abilities are affected by their condition, driving a power wheelchair can become very dangerous, both for themselves and the surrounding environment. This article proposes the use of wearable vibrotactile haptics for wheelchair navigation assistance. We use one or two haptic armbands, each composed of four evenly-spaced vibrotactile actuators, for providing different navigation information to power wheelchair users. With respect to other available solutions, our approach provides rich navigation information while always leaving the patient in control of the wheelchair motion. Moreover, our armbands can be easily adapted for different limbs and can be used by all those patients who are unable to safely maneuver a kinesthetic interface. The results of two human subjects studies show the viability and effectiveness of the proposed technique with respect to not providing any environmental cue. Collisions were reduced by 49% when using the vibrotactile armbands. Moreover, most subjects expressed a preference for receiving haptic feedback and found the armbands comfortable to wear and use.

Mid-air haptic interfaces are promising tools for providing tactile feedback in Virtual Reality (VR) applications, as they do not require the user to be tethered to, hold, or wear any system or device. Currently, focused ultrasound phased arrays are the most mature solution for providing mid-air haptic feedback. They modulate the phase of an array of ultrasound emitters so as to generate focused points of oscillating high pressure, eliciting vibrotactile sensations when encountering a user's skin. While these arrays feature a reasonably large vertical workspace, they are not capable of displaying stimuli far beyond their horizontal limits, severely limiting their workspace in the lateral dimensions. In this paper, we propose an innovative low-cost solution for enlarging the workspace of focused ultrasound arrays. It features two degrees of freedom, rotating the array around the pan and tilt axes, thereby significantly increasing the usable workspace and enabling multi-directional feedback. Our hardware tests and human subject study in an ecological VR setting show a 14-fold increase in workspace volume, with focal point repositioning speeds over 0.85 m/s while delivering tactile feedback with positional accuracy below 18 mm. Finally, we propose a representative use case to exemplify the potential of our system for VR applications.

This letter focuses on finding robust paths for a robotic system by taking into account the state uncertainty and the probability of collision. We are interested in dealing with intermittent exteroceptive measurements (e.g., collected from vision). We assume that these cues provide reliable measurements that will update a state estimation algorithm wherever they are available. The planner has to manage two tasks: reaching the goal in a minimum time and collecting sufficient measurements to reach the goal state with a given confidence level. We present a robust perception-aware bi-directional A* planner for differentially flat systems such as a unicycle and a quadrotor UAV and use a derivative-free Kalman filter to approximate the belief dynamics in the flat space. We also propose an efficient way of ensuring continuity and feasibility by exploiting the convex-hull property of B-spline curves.

This paper studies the combination of tangible objects and wearable haptics for improving the display of stiffness sensations in virtual environments. Tangible objects enable to feel the general shape of objects, but they are often passive or unable to simulate several varying mechanical properties. Wearable haptic devices are portable and unobtrusive interfaces able to generate varying tactile sensations, but they often fail at providing convincing stiff contacts and distributed shape sensations. We propose to combine these two approaches in virtual and augmented reality (VR/AR), becoming able of arbitrarily augmenting the perceived stiffness of real/tangible objects by providing timely tactile stimuli at the fingers. We developed a proof-of-concept enabling to simulate varying elasticity/stiffness sensations when interacting with tangible objects by using wearable tactile modules at the fingertips. We carried out a user study showing that wearable haptic stimulation can well alter the perceived stiffness of real objects, even when the tactile stimuli are not delivered at the contact point. We illustrated our approach both in VR and AR, within several use cases and different tangible settings, such as when touching surfaces, pressing buttons and pistons, or holding an object. Taken together, our results pave the way for novel haptic sensations in VR/AR by better exploiting the multiple ways of providing simple, unobtrusive, and low-cost haptic displays.

In this paper, visual servoing based on photometric moments is advocated. A direct approach is chosen by which the extraction of geometric primitives, visual tracking and image matching steps of a conventional visual servoing pipeline can be bypassed. A vital challenge in photometric methods is the change in the image resulting from the appearance and disappearance of portions of the scene from the camera field of view during the servo. To tackle this issue, a general model for the photometric moments enhanced with spatial weighting is proposed. The interaction matrix for these spatially weighted photometric moments is derived in an analytical form. The correctness of the modeling, effectiveness of the proposed strategy in handling the exogenous regions, and improved convergence domain are demonstrated with a combination of simulation and the experimental results.