--Contact-based estimation of object pose is challenging due to discontinuities and ambiguous observations that can correspond to multiple possible system states. This multimodality makes it difficult to efficiently sample valid hypotheses while respecting contact constraints. Diffusion models can learn to generate samples from such multimodal probability distributions through denoising algorithms. We leverage these probabilistic modeling capabilities to learn an inverse observation model conditioned on tactile measurements acquired from a distributed artificial skin. We present simulated experiments demonstrating efficient sampling of contact hypotheses for object pose estimation through touch.

Tactile sensing is used in robotics to obtain real-time feedback during physical interactions. Fine object manipulation is a robotic application that benefits from a high density of sensors to accurately estimate object pose, whereas a low sensing resolution is sufficient for collision detection. Introducing variable sensing resolution into a single tactile sensing array can increase the range of tactile use cases, but also invokes challenges in localizing internal sensor positions. In this work, we present a mutual capacitance sensor array with variable sensor density, VARSkin, along with a localization method that determines the position of each sensor in the non-uniform array. When tested on two distinct artificial skin patches with concealed sensor layouts, our method achieves a localization accuracy within $\pm 2mm$. We also provide a comprehensive error analysis, offering strategies for further precision improvement.

Estimating the location of contact is a primary function of artificial tactile sensing apparatuses that perceive the environment through touch. Existing contact localization methods use flat geometry and uniform sensor distributions as a simplifying assumption, limiting their ability to be used on 3D surfaces with variable density sensing arrays. This paper studies contact localization on an artificial skin embedded with mutual capacitance tactile sensors, arranged non-uniformly in an unknown distribution along a semi-conical 3D geometry. A fully connected neural network is trained to localize the touching points on the embedded tactile sensors. The studied online model achieves a localization error of $5.7 \pm 3.0$ mm. This research contributes a versatile tool and robust solution for contact localization that is ambiguous in shape and internal sensor distribution.

Researchers have designed a robotic "artificial skin" that is as unique as the team's animal inspiration--the platypus. Created by collaborators between China's Tsinghua University and the Beijing Institute of Nanoenergy and Nanosystems, the dual-sensory system can interpret information not just from direct physical touch, but also through detecting electrostatic changes in the air around it. The platypus is famously recognized for its wide range of zoological oddities. Over millions of years, the egg-laying mammal has evolved a duck bill, webbed feet tipped with tiny, venomous talons, as well as a flat, beaver-like tail. But not all of its notable attributes are physical--the creature also relies on a highly attuned sensory system capable of identifying both mechanical inputs like touch, and electrical shifts in its nearby environment.

Editing human embryos is restricted in much of the world--and making an edited baby is fully illegal in most countries surveyed by legal scholars. But advancing technology could render the embryo issue moot. New ways of adding CRISPR, the revolutionary gene editing tool, to the bodies of people already born could let them easily receive changes as well. It's possible that in 125 years, many people will be the beneficiaries of multiple rare, but useful, gene mutations currently found in only small segments of the population. These could protect us against common diseases and infections, but eventually they could also yield improvements in other traits, such as height, metabolism, or even cognition. But humanity won't necessarily do things the right way.

But if you press harder, you may notice a second way of sensing the touch: through your knuckles and other joints. That sensation–a feeling of torque, to use the robotics jargon–is exactly what the researchers have re-created in their new system. Their robotic arm contains six sensors, each of which can register even incredibly small amounts of pressure against any section of the device. After precisely measuring the amount and angle of that force, a series of algorithms can then map where a person is touching the robot and analyze what exactly they're trying to communicate. For example, a person could draw letters or numbers anywhere on the robotic arm's surface with a finger, and the robot could interpret directions from those movements. Any part of the robot could also be used as a virtual button.

An artificial skin is helping a robot to recognise the difference between picking up inanimate objects and living sea creatures such as starfish and shellfish. That sense of touch could prove useful in cleaning up the ocean, doing underwater exploration or even carrying out deep-sea mining on the seafloor. The artificial skin's sense of touch harnesses what is known as the magnetoelastic effect – changes that occur in the magnetic field of materials as they are pushed and pulled.

An artificial skin is helping a robot to recognise the difference between picking up inanimate objects and living sea creatures such as starfish and shellfish. That sense of touch could prove useful in cleaning up the ocean, doing underwater exploration or even carrying out deep-sea mining on the seafloor. The artificial skin's sense of touch harnesses what is known as the magnetoelastic effect – changes that occur in the magnetic field of materials as they are pushed and pulled.

An artificial skin is even better than human skin at sensing objects, because it can detect and identify items that it hasn't touched yet. "Human skin has to touch something to tell it what is there," says Yifan Wang at Nanyang Technological University in Singapore. "Human skin can only tell the softness or hardness of an object. We wanted our artificial skin to have more functions." Even without touching an object, Wang and his colleagues' artificial skin can sense if it is close by and can also discern some clues about the type of material it is made of.

We tend to take our sense of touch for granted in everyday settings, but it is vital for our ability to interact with our surroundings. Imagine reaching into the fridge to grab an egg for breakfast. As your fingers touch its shell, you can tell the egg is cold, that its shell is smooth, and how firmly you need to grip it to avoid crushing it. These are abilities that robots, even those directly controlled by humans, can struggle with. A new artificial skin developed at Caltech can now give robots the ability to sense temperature, pressure, and even toxic chemicals through a simple touch.