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Autonomous systems face the intricate challenge of navigating unpredictable environments and interacting with external objects. The successful integration of robotic agents into real-world situations hinges on their perception capabilities, which involve amalgamating world models and predictive skills. Effective perception models build upon the fusion of various sensory modalities to probe the surroundings. Deep learning applied to raw sensory modalities offers a viable option. However, learning-based perceptive representations become difficult to interpret. This challenge is particularly pronounced in soft robots, where the compliance of structures and materials makes prediction even harder. Our work addresses this complexity by harnessing a generative model to construct a multi-modal perception model for soft robots and to leverage proprioceptive and visual information to anticipate and interpret contact interactions with external objects. A suite of tools to interpret the perception model is furnished, shedding light on the fusion and prediction processes across multiple sensory inputs after the learning phase. We will delve into the outlooks of the perception model and its implications for control purposes., Comment: IEEE RAS EMBS 10th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2024)

Soft robots offer remarkable adaptability and safety advantages over rigid robots, but modeling their complex, nonlinear dynamics remains challenging. Strain-based models have recently emerged as a promising candidate to describe such systems, however, they tend to be high-dimensional and time consuming. This paper presents a novel model order reduction approach for soft and hybrid robots by combining strain-based modeling with Proper Orthogonal Decomposition (POD). The method identifies optimal coupled strain basis functions -- or mechanical synergies -- from simulation data, enabling the description of soft robot configurations with a minimal number of generalized coordinates. The reduced order model (ROM) achieves substantial dimensionality reduction while preserving accuracy. Rigorous testing demonstrates the interpolation and extrapolation capabilities of the ROM for soft manipulators under static and dynamic conditions. The approach is further validated on a snake-like hyper-redundant rigid manipulator and a closed-chain system with soft and rigid components, illustrating its broad applicability. Finally, the approach is leveraged for shape estimation of a real six-actuator soft manipulator using only two position markers, showcasing its practical utility. This POD-based ROM offers significant computational speed-ups, paving the way for real-time simulation and control of complex soft and hybrid robots.

Perception is essential for the active interaction of physical agents with the external environment. The integration of multiple sensory modalities, such as touch and vision, enhances this perceptual process, creating a more comprehensive and robust understanding of the world. Such fusion is particularly useful for highly deformable bodies such as soft robots. Developing a compact, yet comprehensive state representation from multi-sensory inputs can pave the way for the development of complex control strategies. This paper introduces a perception model that harmonizes data from diverse modalities to build a holistic state representation and assimilate essential information. The model relies on the causality between sensory input and robotic actions, employing a generative model to efficiently compress fused information and predict the next observation. We present, for the first time, a study on how touch can be predicted from vision and proprioception on soft robots, the importance of the cross-modal generation and why this is essential for soft robotic interactions in unstructured environments., Comment: Accepted for presentation at IEEE RoboSoft 2024

In a quantum Stirling heat engine, the heat exchanged with two thermal baths is partly utilized for performing work by redistributing the energy levels of the working substance. We analyze the thermodynamics of a quantum Stirling engine operating in finite time. We develop a model in which a time-dependent potential barrier changes the energy-level structure of the working substance. The process takes place under a constant interaction with the thermal bath. We further show that in the limit of slow operation of the cycle and low temperature, the efficiency of such an engine approaches Carnot efficiency. We also show that the maximum output power , for the strokes that affect the energy levels, is obtained at an intermediate operating speed, demonstrating the importance of a finite-time analysis., Comment: 11 pages, 8 figures

The fragile nature of quantum circuits is a major bottleneck to scalable quantum applications. Operating at cryogenic temperatures, quantum circuits are highly vulnerable to amplifier backaction and external noise. Non-reciprocal microwave devices such as circulators and isolators are used for this purpose. These devices have a considerable footprint in cryostats, limiting the scalability of quantum circuits. We present a compact microwave diode architecture, which exploits the non-linearity of a superconducting flux qubit. At the qubit degeneracy point we experimentally demonstrate a significant difference between the power levels transmitted in opposite directions. The observations align with the proposed theoretical model. At -99 dBm input power, and near the qubit-resonator avoided crossing region, we report the transmission rectification ratio exceeding 90% for a 50 MHz wide frequency range from 6.81 GHz to 6.86 GHz, and over 60% for the 250 MHz range from 6.67 GHz to 6.91 GHz. The presented architecture is compact, and easily scalable towards multiple readout channels, potentially opening up diverse opportunities in quantum information, microwave read-out and optomechanics., Comment: 13 pages, 8 figures

The Josephson junction is a building block of quantum circuits. Its behavior, well understood when treated as an isolated entity, is strongly affected by coupling to an electromagnetic environment. In 1983, Schmid predicted that a Josephson junction shunted by a resistance exceeding the resistance quantum $\mathbf{\textit{R}}_\mathrm{Q} = h/4e^2 \approx 6.45$ k$\mathbf{\Omega}$ for Cooper pairs would become insulating since the phase fluctuations would destroy the coherent Josephson coupling. However, recent microwave measurements have questioned this interpretation. Here, we insert a small Josephson junction in a Johnson-Nyquist-type setup where it is driven by weak current noise arising from thermal fluctuations. Our heat probe minimally perturbs the junction's equilibrium, shedding light on features not visible in charge transport. We find that the Josephson critical current completely vanishes in DC charge transport measurement, and the junction demonstrates Coulomb blockade in agreement with the theory. Surprisingly, thermal transport measurements show that the Josephson junction acts as an inductor at high frequencies, unambiguously demonstrating that a supercurrent survives despite the Coulomb blockade observed in DC measurements. The discrepancy between these two measurements highlights the difference between the low and the high frequency response of a junction and calls for further theoretical and experimental inputs on the dynamics of Josephson junctions \textcolor{black}{operating at high frequencies in highly resistive environments., Comment: Final version accepted for publication

We demonstrate a genuine quantum feature of heat: the power emitted by a qubit (quantum two-level system) into a reservoir under continuous driving shows peaks as a function of frequency $f$. These resonant features appear due to the accumulation of the dynamical phase during the driving. The position of the $n$th maximum is given by $f=f_{\rm M}/n$, where $f_{\rm M}$ is the mean frequency of the qubit in the cycle, and their positions are independent of the form of the drive and the number of heat baths attached, and even the presence or absence of spectral filtering. We show that the waveform of the drive determines the intensity of the peaks, differently for odd and even resonances. This quantum heat is expected to play a crucial role in the performance of driven thermal devices such as quantum heat engines and refrigerators. We also show that by optimizing the cycle protocol, we recover the favorable classical limit in fast driven systems without the use of counter-diabatic drive protocols and we demonstrate an entropy preserving non-unitary process. We propose that this non-trivial quantum heat can be detected by observing the steady-state power absorbed by a resistor acting as a bolometer attached to a driven superconducting qubit., Comment: 6 pages, 3 figures, comments welcome

Superconducting circuits provide a favorable platform for quantum thermodynamic experiments. An important component for such experiments is a heat valve, i.e. a device which allows one to control the heat power flowing through the system. Here we theoretically study the heat valve based on a superconducting quantum interference device (SQUID) coupled to two heat baths via two resonators. The heat current in such system can be tuned by magnetic flux. We investigate how does the heat current modulation depend on the coupling strength g between the SQUID and the resonators. In the weak coupling regime the heat current modulation grows as g2, but, surprisingly, at the intermediate coupling it can be strongly suppressed. This effect is linked to the resonant nature of the heat transport at weak coupling, where the heat current dependence on the magnetic flux is a periodic set of narrow peaks. At the intermediate coupling, the peaks become broader and overlap, thus reducing the heat modulation. At very strong coupling the heat modulation grows again and finally saturates at a constant value., Comment: 8 pages, 3 figures

Soft robots are typically approximated as low-dimensional systems, especially when learning-based methods are used. This leads to models that are limited in their capability to predict the large number of deformation modes and interactions that a soft robot can have. In this work, we present a deep-learning methodology to learn high-dimensional visual models of a soft robot combining multimodal sensorimotor information. The models are learned in an end-to-end fashion, thereby requiring no intermediate sensor processing or grounding of data. The capabilities and advantages of such a modelling approach are shown on a soft anthropomorphic finger with embedded soft sensors. We also show that how such an approach can be extended to develop higher level cognitive functions like identification of the self and the external environment and acquiring object manipulation skills. This work is a step towards the integration of soft robotics and developmental robotics architectures to create the next generation of intelligent soft robots., Comment: Under review in IROS 2022

Quantum heat transport devices are currently intensively studied in theory. Experimental realization of quantum heat transport devices is a challenging task. So far, they have been mostly investigated in experiments with ultra-cold atoms and single atomic traps. Experiments with superconducting qubits have also been carried out and heat transport and heat rectification has been studied in two terminal devices. The structures with three independent terminals offer additional opportunities for realization of heat transistors, heat switches, on-chip masers and even more complicated devices. Here we report an experimental realization of a three-terminal photonic heat transport device based on a superconducting quantum circuit. Its central element is a flux qubit made of a superconducting loop containing three Josephson junctions, which is connected to three resonators terminated by resistors. By heating one of the resistors and monitoring the temperatures of the other two, we determine photonic heat currents in the system and demonstrate their tunability by magnetic field at the level of 1 aW. We determine system parameters by performing microwave transmission measurements on a separate nominally identical sample and, in this way, demonstrate clear correlation between the level splitting of the qubit and the heat currents flowing through it. Our experiment is an important step in the development of on-chip quantum heat transport devices. On the one hand, such devices are of great interest for fundamental science because they allow one to investigate the effect of quantum interference and entanglement on the transport of heat. On the other hand, they also have great practical importance for the rapidly developing field of quantum computing, in which management of heat generated by qubits is a problem., Comment: 10 pages, 7 figures