12 accepted papers
Recent advances in machine learning have driven a step-change in robot perception with modalities such as vision, where large amounts of training data are readily available or cheap to collect. However, in tactile perception, the relatively high cost of data collection still largely impedes the adop
For several tasks, ranging from manipulation to inspection, it is beneficial for robots to localize a target object in their surroundings. In this paper, we propose an approach that utilizes coarse point clouds obtained from miniaturized VL53L5CX Time-of-Flight (ToF) sensors (tiny LiDARs) to localiz
Robots performing tasks in challenging environments must be supported by control or planning algorithms that exploit sensor feedback to effectively plan the robot’s actions. In this paper, we propose a reactive control law that simultaneously utilizes proximity and tactile feedback to perform a pick…
Recent developments in vision-based tactile sensing offer a simple means to enable robots to perceive touch interactions. However, existing sensors are primarily designed for small-scale applications like robotic hands, lacking research on their integration for large-sized robot bodies that can be l…
Intubation is essential for ventilating critically ill patients and involves precise maneuvering of a laryngoscope to place an endotracheal tube (ETT). However, training for this procedure is fraught with challenges. Traditional methods, relying on manikins or training with a single sensing modality…
The Peg-In-Hole (PiH) task performed under un-certain conditions still represents a challenge for autonomous robots. When the peg is not rigidly connected to the robot end-effector, the external forces generated by peg-environment interactions can change the in-hand pose of the peg. This aspect must…
Humans rely on distributed tactile sensing in their hands to achieve robust and dexterous manipulation of delicate objects. Soft robotic hands have received increased attention in recent years due to their adaptability to unknown objects and safe interactions with the environment. However, the integ
Tactile perception is key for robotics applications such as manipulation. However, tactile data collection is time-consuming, especially when compared to vision. This limits the use of the tactile modality in machine learning solutions in robotics. In this paper, we propose a generative model to sim…
Algorithms for tactile data processing heavily rely on the generation of tactile images representing the contact pressure distribution. This approach allows to exploit existing algorithms for image processing, but requires the integration of the tactile elements on a flat surface. Robot skin technol
Robots operating in unstructured environments must be capable of safely handling unexpected collisions with objects existing in the surrounding area, possibly without stopping the task execution. This letter proposes a tactile feedback control law allowing the robot to apply bounded contact forces i
This paper deals with the problem of using the tactile feedback generated by a robotic skin for discriminating a human hand touch from a generic contact. Humans understand collaboration intentions through different sensing modalities such as vision, hearing and touch. Among them, a physical interact…
This paper deals with the problem of estimating the pose of tactile elements (i.e. taxels) composing a robotic skin covering the whole body of a robot. This problem arises when a robot skin technology has to be integrated into an already existing robotic platform. To date, the integration process is…