Related papers: Enhanced Model-Free Dynamic State Estimation for a…
In contrast to conventional robots, accurately modeling the kinematics and statics of continuum robots is challenging due to partially unknown material properties, parasitic effects, or unknown forces acting on the continuous body.…
A sensor-fused wearable assistance prototype for upper-limb function (triceps brachii and extensor pollicis brevis) is presented. The device integrates surface electromyography (sEMG), an inertial measurement unit (IMU), and flex/force…
Estimating the impact intensity is one of the significant tasks of the legged robot. Accurate feedback of the impact may support the robot to plan a suitable and efficient trajectory to adapt to unknown complex terrains. Ordinarily, this…
Compliant grippers enable robots to work with humans in unstructured environments. In general, these grippers can improve with tactile sensing to estimate the state of objects around them to precisely manipulate objects. However,…
Object insertion tasks are prone to failure under pose uncertainty and environmental variation, often requiring manual fine-tuning or controller retraining. We present a novel approach for robust and resilient object insertion using a…
This study addresses the absence of an identification framework to quantify a comprehensive dynamic model of human and anthropomorphic tendon-driven fingers, which is necessary to investigate the physiological properties of human fingers…
Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack of information provided by current tactile sensors. In this…
Robust closed-loop locomotion remains challenging for soft quadruped robots due to high-dimensional dynamics, actuator hysteresis, and difficult-to-model contact interactions, while conventional proprioception provides limited information…
Autonomous nano-drones (~10 cm in diameter), thanks to their ultra-low power TinyML-based brains, are capable of coping with real-world environments. However, due to their simplified sensors and compute units, they are still far from the…
In this paper, we present a novel factor graph formulation to estimate the pose and velocity of a quadruped robot on slippery and deformable terrain. The factor graph introduces a preintegrated velocity factor that incorporates velocity…
In this paper, we address the problem of controlling a network of mobile sensors so that a set of hidden states are estimated up to a user-specified accuracy. The sensors take measurements and fuse them online using an Information Consensus…
The morphology of a slender soft-robot can be modified by sensing its shape via sensors and exerting moments via actuators embedded along its body. The actuating moments required to morph these soft-robots to a desired shape are often…
Finite element methods have been successfully used to develop physics-based models of soft robots that capture the nonlinear dynamic behavior induced by continuous deformation. These high-fidelity models are therefore ideal for designing…
State-of-the-art robotic perception systems have achieved sufficiently good performance using Inertial Measurement Units (IMUs), cameras, and nonlinear optimization techniques, that they are now being deployed as technologies. However, many…
This paper proposes a novel pneumatic soft robotic hand that incorporates a mechanism that can switch the airflow path using a single airflow control. The developed hand can control the finger motion and operate the surface friction…
Assistive electric-powered wheelchairs (EPWs) have become essential mobility aids for people with disabilities such as amyotrophic lateral sclerosis (ALS), post-stroke hemiplegia, and dementia-related mobility impairment. This work presents…
Camera-based tactile sensors provide robots with a high-performance tactile sensing approach for environment perception and dexterous manipulation. However, achieving comprehensive environmental perception still requires cooperation with…
While gesture recognition using vision or robot skins is an active research area in Human-Robot Collaboration (HRC), this paper explores deep learning methods relying solely on a robot's built-in joint sensors, eliminating the need for…
The growing availability of the data collected from smart manufacturing is changing the paradigms of production monitoring and control. The increasing complexity and content of the wafer manufacturing process in addition to the time-varying…
The compliant nature of soft wearable robots makes them ideal for complex multiple degrees of freedom (DoF) joints, but also introduce additional structural nonlinearities. Intuitive control of these wearable robots requires robust sensing…