23 accepted papers
Accurate human pose estimation is essential for effective Human-Robot Interaction (HRI). By observing a user's arm movements, robots can respond appropriately, whether it's providing assistance or avoiding collisions. While visual perception offers potential for human pose estimation, it can be hind
Compared to rigid hands, underactuated compliant hands offer greater adaptability to object shapes, provide stable grasps, and are often more cost-effective. However, they introduce uncertainties in hand-object interactions due to their inherent compliance and lack of precise finger proprioception a
Object recognition, commonly performed by a camera, is a fundamental requirement for robots to complete complex tasks. Some tasks require recognizing objects far from the robot's camera. A challenging example is Ultra-Range Gesture Recognition (URGR) in human-robot interaction where the user exhibit
Tactile sensing is a necessary capability for a robotic hand to perform fine manipulations and interact with the environment. Optical sensors are a promising solution for high-resolution contact estimation. Nevertheless, they are usually not easy to fabricate and require individual calibration in or
Simulating tactile perception could potentially leverage the learning capabilities of robotic systems in manipulation tasks. However, the reality gap of simulators for high-resolution tactile sensors remains large. Models trained on simulated data often fail in zero-shot inference and require fine-t…
Robotic arms are highly common in various automation processes such as manufacturing lines. However, these highly capable robots are usually degraded to simple repetitive tasks such as pick-and-place. On the other hand, designing an optimal robot for one specific task consumes large resources of eng…
Tendon-based underactuated hands are intended to be simple, compliant and affordable. Often, they are 3D printed and do not include tactile sensors. Hence, performing in-hand object recognition with direct touch sensing is not feasible. Adding tactile sensors can complicate the hardware and introduc…
Modern manipulators are acclaimed for their precision but often struggle to operate in confined spaces. This limitation has driven the development of hyper-redundant and continuum robots. While these present unique advantages, they face challenges in, for instance, weight, mechanical complexity, mod
Teleoperation enables a user to perform dangerous tasks (e.g., work in disaster zones or in chemical plants) from a remote location. Nevertheless, common approaches often provide cumbersome and unnatural usage. In this letter, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:x
Object insertion is primarily studied using rigid robotic hands. However, these may have difficulties overcoming spatial uncertainties originating from an uncertain initial grasp. Compliant hands, on the other hand, can cope with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:x
Throwing objects by a robot extends its reach and has many industrial applications. While analytical models can provide efficient performance, they require accurate estimation of system parameters. Reinforcement Learning (RL) algorithms can provide an accurate throwing policy without prior knowledge
The dual-arm manipulation of elastic wires has been a hard problem for many decades. Nevertheless, recent work has shown that the shape of a wire can be defined by a very simple representation. Theoretical analysis has stated that simple sensing of the force and torque at one end of the wire can be
Applicable human-robot collaboration requires intuitive recognition of human intention during shared work. A grasped object such as a tool held by the human provides vital information about the upcoming task. In this letter, we explore the use of a wearable device to non-visually recognize objects w
Feasible human-robot collaboration requires intuitive and fluent understanding of human motion in shared tasks. The object in hand provides the most valuable information about the intended task of a human. In this letter, we propose a simple and affordable approach where a wearable force-myography d
Transfer learning is a popular approach to bypassing data limitations in one domain by leveraging data from another domain. This is especially useful in robotics, as it allows practitioners to reduce data collection with physical robots, which can be time-consuming and cause wear and tear. The most…
We present a novel motion planning strategy for the manipulation of elastic rods with two robotic arms. In previous work, it has been shown that the free configuration space of an elastic rod, i.e., the set of equilibrium shapes of the rod, is a smooth manifold of a finite dimension that can be para
Underactuated adaptive hands simplify grasping tasks but it is difficult to model their interactions with objects during in-hand manipulation. Learned data-driven models have been recently shown to be efficient in motion planning and control of such hands. Still, the accuracy of the models is limite…
Many manipulation tasks, such as placement or within-hand manipulation, require the object's pose relative to a robot hand. The task is difficult when the hand significantly occludes the object. It is especially hard for adaptive hands, for which it is not easy to detect the finger's configuration.…
Fully actuated multifingered robotic hands are often expensive and fragile. Low-cost underactuated hands are appealing but present challenges due to the lack of analytical models. This letter aims to learn a stochastic version of such models automatically from data with minimum user effort. The focu
This paper focuses on tracking failure avoidance during vision-based navigation to a desired goal in unknown environments. While using feature-based Visual Simultaneous Localization and Mapping (VSLAM), continuous identification and association of map points are required during motion. Thus, we disc…
This letter provides a comparative analysis of common strategies for sampling-based motion planning of fully actuated closed kinematic chains with revolute joints. Three strategies are reviewed: singularity sampling, swapping between the possible passive chains while using the active-passive chains
In this paper we propose an energy control based algorithm for performing swing-up regrasping. In such regrasping motion, an object is manipulated using a robotic arm around a point pinched by the arms gripper. The aim is to manipulate the object from an initial angle to regrasp it on a new desired
A novel algorithm is proposed for offline motion planning of a robotic arm to perform a throw task of an object to reach a goal target. The planning algorithm searches for a throw trajectory that could be performed under kinematic and dynamic (i.e., kinodynamic) constraints. We parameterize the thro…