Visual Inertial Odometry (VIO) and Simultaneous Localization and Mapping (SLAM) have experienced increasing interest in both the consumer and racing automotive sectors in recent decades. With the introduction of novel neuromorphic vision sensors, it is now possible to accurately localize a vehicle even under complex environmental conditions, leading to an improved and safer driving experience. In this paper, we propose MA-VIED, a large-scale driving dataset that collects race track-like loops, maneuvers, and standard driving scenarios, all bundled in a rich sensory dataset. MA-VIED provides highly accurate IMU data, standard and event camera streams, and RTK position data from a dual GPS antenna, both of which are hardware-synchronized with all cameras and IMU data. In addition, we collect accurate wheel odometry data and other data from the vehicle’s CAN bus. The dataset contains 13 sequences collected in urban, suburban, and racetrack-like environments with varying lighting conditions and driving dynamics. We provide ground-truth RTK data for algorithms evaluation and the calibration sequences for both IMU and cameras. We then present three tests to demonstrate how MA-VIED can be suitable for monocular VIO applications, using state-of-the-art VIO algorithms and an EKF-based sensor fusion solution. The experimental results show that MA-VIED can support the development and prototyping of novel automotive-oriented frame and event-based monocular VIO algorithms.

Robots have replaced people in many manufacturing production lines but the information they gather from sensors might not be sufficient to autonomously accomplish dexterous manipulation operations. Symbiotic human-robot cooperation appears to be a more realistic near future in industrial scenarios. In this paper we present a configuration of human-robot collaboration in which the robot is sensory-augmented by means of a set of tactile signals coming from the human operator. The incorporation of low-level robot “intelligence” permits the cooperative manipulation of an object while enabling the human operator to stay focused on task itself and carry it out in the most natural way. The effectiveness of this approach is demonstrated in a use case in which a robot helps a human operator to successfully accomplish a writing task. System performance has been evaluated, considering several positions of the tiny vibration sensor in charge of gathering the human perception, by testing it on both the human hand and the co-manipulated object. Results suggest that the sensor provides valuable information for recognizing operator actions when it is placed either on the human hand or on the co-manipulated object. However, the sensor on the finger directly represents the operator's perception, while the output of the sensor attached to the object changes according to the distance between the interaction point and the sensor itself. In addition, in wearing the sensor, neither the object nor the robot need to be instrumented: the operator is free to interact with a large set of objects and collaborate with any existing robot without requiring supplemental equipment.

Haptic systems have only recently started to be designed with wearability in mind. Compact, unobtrusive, inexpensive, easy-to-wear, and lightweight haptic devices enable researchers to provide compelling touch sensations to multiple parts of the body, significantly increasing the applicability of haptics in many fields, such as robotics, rehabilitation, gaming, and immersive systems. In this respect, wearable haptics has a great potential in the fields of virtual and augmented reality. Being able to touch virtual objects in a wearable and unobtrusive way may indeed open new exciting avenues for the fields of haptics and VR. This work presents a novel wearable haptic system for immersive virtual reality experiences. It conveys the sensation of touching objects made of different materials, rendering pressure and texture stimuli through a moving platform and a vibrotactile abbrv-doi-hyperref-narrowmotor. The device is composed of two platforms: one placed on the nail side of the finger and one in contact with the finger pad, connected by three cables. One small servomotor controls the length of the cables, moving the platform towards or away from the fingertip. One voice coil actuator, embedded in the platform, provides vibrotactile stimuli to the user.

We present Hand in Air Tapping (HAT), a wearable input interface which allows interactions through fingers tapping. It consists in a Bluetooth Low Energy rings enabling wireless communication with any compatible device. Each ring is hardware-wise independent of the others. This allows full modularity, i.e., the number of employed devices can be chosen to meet each application requirements. The proposed system was evaluated in two user studies, both on text input: (1) users learning curve in terms of writing speed; (2) rate of text entry comparison between the proposed interface and that of numpad style keyboards. We associated each keystroke to a set of letters/symbols and compared two approaches: one based on T9 technique and the other on multi-tap input method. Results show comparable performance between HAT and numpad style keyboards. HAT keeps the hands free, not affecting hand movements and human interactions with the surroundings. Moreover, as a general input technology, it might have several potential applications in the field of computer-human interfaces.

The human hand represents a complex fascinating system with highly sensitive sensory capabilities and dexterous grasping and manipulation functionalities. As a consequence, estimating the hand pose and at the same time having the capability to provide haptic feedback in a wearable way may benefit areas such as rehabilitation, human-robot interaction, gaming, and many more. Existing solutions allow us to accurately measure the hand configuration and provide effective force feedback to the user. However, they have limited wearability/portability. In this paper, we present the wearable sensing/actuation system glove for enhanced sensing and touching (GESTO). It is based on inertial and magnetic sensors for hand tracking, coupled with cutaneous devices for the force feedback rendering. Unlike vision-based tracking systems, the sensing glove does not suffer from occlusion problems and lighting conditions. We properly designed the cutaneous devices in order to reduce possible interferences with the magnetic sensors and performed an experimental validation on ten healthy subjects. In order to measure the estimation accuracy of GESTO, we used a high-precision optical tracker. A comparison between using the glove with and without the haptic devices shows that the presence of them does not induce a statistically significant increase in the estimation error. Experimental results revealed the effectiveness of the proposed approach. The accuracy of our system, 3.32° mean estimation error in the worst case, is comparable with the human ability of discriminating finger joint angle.

Bilateral telemanipulation refers to frameworks in which a human operator manipulates a master robotic interface and a slave robotic device emulates the behavior of the master, while haptic feedback is provided to the operator. For multi-contact bilateral teleoperation wc intend master and slave systems that can establish multiple contact points with the user and with the environment. A paradigmatic example can be a multi-lingered robotic hand teleoperated by the human hand. Two of the most critical issues in this context are: (i) how to provide haptic feedback on multiple points of the human hand; (ii) how to solve the correspondence problem between the human hand and the robotic slave device. In this work, we propose finger-worn devices able to apply a three dimensional vector of force at a specific contact point to solve the multicontact feedback problem. For the correspondence problem, we propose an object-based mapping procedure. The approach is based on two virtual objects, defined both at the master and slave sides, to capture the human hand motion and to compute the related force feedback. The proposed approach has been tested in a telemanipulation framework where the master side was composed of a Leap Motion sensor used to track the hand plus three wearable haptic devices, while a robotic hand/arm system performed a manipulation task as slave.

Wearable robots have been mostly designed as exoskeletons, with segments and joints corresponding to those of the person they are coupled with. Exoskeletons are mainly employed to augment human body force and precision capabilities, or for rehabilitation purposes. More recently, new wearable robots resembling additional robotic limbs have been developed thanks to the progress in miniaturization and efficiency of mechanical and sensing components. However, wearable robotic extra limbs presented in the literature lack of effective haptic feedback systems. In this paper, we present a robotic extra finger coupled with a vibrotactile ring interface. The human user is able to control the motion of the robotic finger through a switch placed on the ring, while being provided with vibrotactile feedback about the forces exerted by the robotic finger on the environment. To understand how to control the vibrotactile interface to evoke the most effective cutaneous sensations, we executed perceptual experiments to evaluate its absolute and differential thresholds. We also carried out a pick-and-place experiment with ten subjects. Haptic feedback significantly improved the performance in task execution in terms of completion time, exerted force, and perceived effectiveness. All subjects preferred experimental conditions employing haptic feedback with respect to those not providing any force feedback.

This paper presents a bilateral telemanipulation framework where the master and slave sub-systems have different kinematic structures. A virtual object is defined on the master and slave sides and used to capture the human hand motion and to compute the related force feedback. The force feedback is determined imposing that the same wrench acts on the master and slave virtual objects. An abstraction from the sub-system structures is obtained focusing on the effects produced on the manipulated object. The proposed approach has been tested with an experimental setup consisting of two haptic interfaces able to capture index and thumb motions on the master side and a DLR-HIT Hand II as slave sub-system.