Related papers: Human-Inspired Soft Anthropomorphic Hand System fo…
Soft robotics is a thriving branch of robotics which takes inspiration from nature and uses affordable flexible materials to design adaptable non-rigid robots. However, their flexible behavior makes these robots hard to model, which is…
To touch and be touched are vital to human development, well being, and relationships. However, to those who have lost their arms and hands due to accident or war, touching becomes a serious concern that often leads to psychosocial issues…
Deep learning inference that needs to largely take place on the 'edge' is a highly computational and memory intensive workload, making it intractable for low-power, embedded platforms such as mobile nodes and remote security applications.…
In this paper, we present a touch technology to achieve tactile interactivity for human-robot interaction (HRI) in soft robotics. By combining a capacitive touch sensor with an online solid mechanics simulation provided by the SOFA…
In brain-machine interface (BMI) applications, a key challenge is the low information content and high noise level in neural signals, severely affecting stable robotic control. To address this challenge, we proposes a cooperative shared…
Humans display the remarkable ability to sense the world through tools and other held objects. For example, we are able to pinpoint impact locations on a held rod and tell apart different textures using a rigid probe. In this work, we…
Conventional industrial robots often use two-fingered grippers or suction cups to manipulate objects or interact with the world. Because of their simplified design, they are unable to reproduce the dexterity of human hands when manipulating…
Coordinated human movement depends on the integration of multisensory inputs, sensorimotor transformation, and motor execution, as well as sensory feedback resulting from body-environment interaction. Building dynamic models of the…
This paper describes a system for transmitting softness and the motion of shape or contact area sensation using a vision based tactile sensor and a tactile display in which mechanical and electrical stimulation are combined. A unit of…
Tracking and acquiring simultaneous optical images of randomly moving targets obscured by scattering media remains a challenging problem of importance to many applications that require precise object localization and identification. In this…
Tactile sensing is a essential for skilled manipulation and object perception, but existing devices are unable to capture mechanical signals in the full gamut of regimes that are important for human touch sensing, and are unable to emulate…
Brain-computer interface allows people who have lost their motor skills to control robot limbs based on electroencephalography. Most BCIs are guided only by visual feedback and do not have somatosensory feedback, which is an important…
Human-to-Robot handovers are useful for many Human-Robot Interaction scenarios. It is important to recognize when a human intends to initiate handovers, so that the robot does not try to take objects from humans when a handover is not…
In this paper, we propose the development of an interactive platform between humans and a dual-arm robotic system based on the Robot Operating System (ROS) and a multimodal artificial intelligence model. Our proposed platform consists of…
We introduce SonicSense, a holistic design of hardware and software to enable rich robot object perception through in-hand acoustic vibration sensing. While previous studies have shown promising results with acoustic sensing for object…
While parallel grippers and multi-fingered robotic hands are well developed and commonly used in structured settings, it remains a challenge in robotics to design a highly articulated robotic hand that can be comparable to human hands to…
Recent advances in the field of intelligent robotic manipulation pursue providing robotic hands with touch sensitivity. Haptic perception encompasses the sensing modalities encountered in the sense of touch (e.g., tactile and kinesthetic…
We outline the design and construction of novel robotic arms using machine perception, convolutional neural networks, and symbolic AI for logical control and affordance indexing. We describe our robotic arms built with a humanlike…
Neuromorphic Computing (NC) and Spiking Neural Networks (SNNs) in particular are often viewed as the next generation of Neural Networks (NNs). NC is a novel bio-inspired paradigm for energy efficient neural computation, often relying on…
We propose a neuromorphic tactile sensing framework for robotic texture classification that is inspired by human exploratory strategies. Our system utilizes the NeuroTac sensor to capture neuromorphic tactile data during a series of…