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Autonomous robot navigation in complex environments requires robust perception as well as high-level scene understanding due to perceptual challenges, such as occlusions, and uncertainty introduced by robot movement. For example, a robot climbing a cluttered staircase can misinterpret clutter as a step, misrepresenting the state and compromising safety. This requires robust state estimation methods capable of inferring the underlying structure of the environment even from incomplete sensor data. In this paper, we introduce a novel method for robust state estimation of staircases. To address the challenge of perceiving occluded staircases extending beyond the robot's field-of-view, our approach combines an infinite-width staircase representation with a finite endpoint state to capture the overall staircase structure. This representation is integrated into a Bayesian inference framework to fuse noisy measurements enabling accurate estimation of staircase location even with partial observations and occlusions. Additionally, we present a segmentation algorithm that works in conjunction with the staircase estimation pipeline to accurately identify clutter-free regions on a staircase. Our method is extensively evaluated on real robot across diverse staircases, demonstrating significant improvements in estimation accuracy and segmentation performance compared to baseline approaches., Comment: This work has been submitted to the IEEE for possible publication

As technology advances, the integration of physical, virtual, and social worlds has led to a complex landscape of ``Realities'' such as Virtual Reality (VR), Augmented Reality (AR), metaverse, spatial computing, and other emerging paradigms. This paper builds upon and refines the concept of eXtended Reality (XR) as the unifying framework that not only interpolates across these diverse realities but also extrapolates (extends) to create entirely new possibilities. XR is the ``physical spatial metaverse,'' bridging the physical world, the virtual world of artificial intelligence, and the social world of human interaction. These three worlds define the Socio-Cyber-Physical Taxonomy of XR that allows us to identify underexplored research areas such as Diminished Reality (DR), and chart future directions to {\bf advance technology for people and planet}. We highlight the six core properties of XR for applications in sustainability, healthcare, frontline work, and daily life. Central to this vision is the development of AI-driven wearable technologies, such as the smart eyeglass, that sustainably extend human capabilities., Comment: 9 pages, 9 figures, getting ready for the panel discussion at IEEE ICCE

Supercontinuum generation in the ultraviolet spectral region is challenging in solid-core optical fibres due to solarization and photodarkening. Antiresonant hollow-core fibres have overcome this limitation and have been shown to guide ultraviolet light at sufficient intensity for ultraviolet spectral broadening through nonlinear optics in the filling gas. However, their ultraviolet guidance is usually limited by discontinuities caused by the presence of high-loss resonance bands. In this paper, we report on resonance-free supercontinuum generation spanning from the deep ultraviolet to the near infrared achieved through modulation instability in an argon-filled antiresonant hollow-core fibre. The fibre was directly fabricated using the stack-and-draw method with a wall thickness of approximately 90 nm, enabling continuous spectral coverage from the deep ultraviolet to the near infrared. We also report numerical simulations to investigate the supercontinuum bandwidth and the factors limiting it, finding that the overall dispersion landscape, and associated group-velocity matching of cross-phase modulation interactions, is the dominant constraint on spectral extension.

We report the generation of a multi-octave supercontinuum spanning from 350 nm to 1700 nm with exceptional spectral flatness and high conversion efficiency to both the visible and near infrared region, by pumping a methane-filled hollow-core antiresonant fiber with 1030 nm laser pulses. The dynamics exhibited signs of both modulational instability and stimulated Raman scattering. Fiber lengths ranging from 15 to 200~cm were investigated along with gas pressures up to 50 bar and pump pulse durations from 220~fs up to 10~ps. The best supercontinuum, in terms of spectral width and flatness, was achieved with 220~fs pulses, 25~bar filling pressure, and 60~cm propagation length. Comparison with argon-filled fiber with matched nonlinearity and dispersion showed that the Raman contribution enhances the supercontinuum generation process compared to a pure modulational instability-based process. The average power was scaled up by increasing the pulse repetition rate to 50~kHz, but further scaling was hindered by linear and nonlinear absorption leading to fiber damage.

We introduce a LiDAR inertial odometry (LIO) framework, called LiPO, that enables direct comparisons of different iterative closest point (ICP) point cloud registration methods. The two common ICP methods we compare are point-to-point (P2P) and point-to-feature (P2F). In our experience, within the context of LIO, P2F-ICP results in less drift and improved mapping accuracy when robots move aggressively through challenging environments when compared to P2P-ICP. However, P2F-ICP methods require more hand-tuned hyper-parameters that make P2F-ICP less general across all environments and motions. In real-world field robotics applications where robots are used across different environments, more general P2P-ICP methods may be preferred despite increased drift. In this paper, we seek to better quantify the trade-off between P2P-ICP and P2F-ICP to help inform when each method should be used. To explore this trade-off, we use LiPO to directly compare ICP methods and test on relevant benchmark datasets as well as on our custom unpiloted ground vehicle (UGV). We find that overall, P2F-ICP has reduced drift and improved mapping accuracy, but, P2P-ICP is more consistent across all environments and motions with minimal drift increase., Comment: Submitted to ICRA 2025

Accurate detection and characterization of nanoparticles within confined spaces is crucial for applications ranging from nanofluidics to biotechnology. We present a novel approach that combines interferometric scattering (iSCAT) detection with trapping by dielectrophoresis (DEP) to achieve label-free detection of nanoparticles that are trapped and/or actuated between nano-gap electrodes. DEP utilizes the interaction between the induced dipole of the particle and the applied electric field to create a trapping potential. We demonstrate our method by trapping and label-free detection of down to 20 nm polystyrene nanoparticles. Additionally, we demonstrate that the signal-to-noise ratio of our detection can be boosted up to 20-fold by periodic actuation of the nanoparticle in the trap. This is done by a digital lock-in detection scheme on the modulated scattering signal. Our method holds promise for various applications, including assembly of nanoparticles, single-particle property analysis, and nanofluidic devices.

Field robotics applications, such as search and rescue, involve robots operating in large, unknown areas. These environments present unique challenges that compound the difficulties faced by a robot operator. The use of multi-robot teams, assisted by carefully designed autonomy, help reduce operator workload and allow the operator to effectively coordinate robot capabilities. In this work, we present a system architecture designed to optimize both robot autonomy and the operator experience in multi-robot scenarios. Drawing on lessons learned from our team's participation in the DARPA SubT Challenge, our architecture emphasizes modularity and interoperability. We empower the operator by allowing for adjustable levels of autonomy ("sliding mode autonomy"). We enhance the operator experience by using intuitive, adaptive interfaces that suggest context-aware actions to simplify control. Finally, we describe how the proposed architecture enables streamlined development of new capabilities for effective deployment of robot autonomy in the field., Comment: Accepted to the IEEE ICRA Workshop on Field Robotics 2024

Ultrafast laser sources in the far ultraviolet (100 nm to 300 nm) have been the subject of intense experimental efforts for several decades, driven primarily by the requirements of advanced experiments in ultrafast science. Resonant dispersive wave emission from high-energy laser pulses undergoing soliton self-compression in a gas-filled hollow capillary fibre promises to meet several of these requirements for the first time, most importantly by combining wide-ranging wavelength tuneability with the generation of extremely short pulses. In this Perspective, we give an overview of this approach to ultrafast far-ultraviolet sources, including its historical origin and underlying physical mechanism, the state of the art and current challenges, and our view of potential applications both within and beyond ultrafast science., Comment: 16 pages, 5 figures

Centralized control of a multi-agent system improves upon distributed control especially when multiple agents share a common task e.g., sorting different materials in a recycling facility. Traditionally, each agent in a sorting facility is tuned individually which leads to suboptimal performance if one agent is less efficient than the others. Centralized control overcomes this bottleneck by leveraging global system state information, but it can be computationally expensive. In this work, we propose a novel framework called Longitudinal Control Volumes (LCV) to model the flow of material in a recycling facility. We then employ a Kalman Filter that incorporates local measurements of materials into a global estimation of the material flow in the system. We utilize a model predictive control algorithm that optimizes the rate of material flow using the global state estimate in real-time. We show that our proposed framework outperforms distributed control methods by 40-100% in simulation and physical experiments., Comment: Accepted to be published at ICRA 2024

The nature of the insulator-to-metal phase transition in vanadium dioxide (VO2) is one of the longest-standing problems in condensed-matter physics. Ultrafast spectroscopy has long promised to determine whether the transition is primarily driven by the electronic or structural degree of freedom, but measurements to date have been stymied by their sensitivity to only one of these components and/or their limited temporal resolution. Here we use ultra-broadband few-femtosecond pump-probe spectroscopy to resolve the electronic and structural phase transitions in VO2 at their fundamental time scales. We find that the system transforms into a bad-metallic phase within 10 fs after photoexcitation, but requires another 100 fs to complete the transition, during which we observe electronic oscillations and a partial re-opening of the bandgap, signalling a transient semi-metallic state. Comparisons with tensor-network simulations and density-functional theory calculations show these features originate from oscillations around the equilibrium high-symmetry atomic positions during an unprecedentedly fast structural transition, in which the vanadium dimers separate and untwist with two different timescales. Our results resolve the complete structural and electronic nature of the light-induced phase transition in VO2 and establish ultra-broadband few-femtosecond spectroscopy as a powerful new tool for studying quantum materials out of equilibrium., Comment: 20 pages, 12 figures

High-order harmonic generation (HHG) arising from the non-perturbative interaction of intense light fields with matter constitutes a well-established tabletop source of coherent extreme-ultraviolet and soft X-ray radiation, which is typically emitted as attosecond pulse trains. However, ultrafast applications increasingly demand isolated attosecond pulses (IAPs), which offer great promise for advancing precision control of electron dynamics. Yet, the direct generation of IAPs typically requires the synthesis of near-single-cycle intense driving fields, which is technologically challenging. In this work, we theoretically demonstrate a novel scheme for the straightforward and compact generation of IAPs from multi-cycle infrared drivers using hollow capillary fibers (HCFs). Starting from a standard, intense multi-cycle infrared pulse, a light transient is generated by extreme soliton self-compression in a HCF with decreasing pressure, and is subsequently used to drive HHG in a gas target. Owing to the sub-cycle confinement of the HHG process, high-contrast IAPs are continuously emitted almost independently of the carrier-envelope phase (CEP) of the optimally self-compressed drivers. This results in a CEP-robust scheme which is also stable under macroscopic propagation of the high harmonics in a gas target. Our results open the way to a new generation of integrated all-fiber IAP sources, overcoming the efficiency limitations of usual gating techniques for multi-cycle drivers., Comment: 18 pages, 5 figures

Fe$_{1.057(7)}$Te undergoes a first-order tetragonal to monoclinc structural transition at T$_{S} \sim 70$ K, breaking the C$_{4}$ lattice symmetry and simultaneously breaking time reversal symmetry with bicollinear magnetic order. We investigate the soft acoustic lattice dynamics near this combined magneto-structural transition. We apply spherically neutron polarimetry to study the static magnetism near this transition, characterized with x-ray powder diffraction, and find no evidence of static incommensurate magnetic correlations near the onset of monoclinic and bicollinear antiferromagnetic order. This fixes the position of our single crystal sample in the Fe$_{1+x}$Te phase diagram in the magnetic bicollinear region and illustrates that our sample statically undergoes a transition from a paramagnetic phase to a low-temperature bicollinear phase. We then apply neutron spectroscopy to study the acoustic phonons, related to elastic deformations of the lattice. We find a temperature dependent soft acoustic branch for phonons propagating along [010] and polarized along [100]. The slope of this acoustic phonon branch is sensitive to the elastic constant $C_{66}$ and the shear modulus. The temperature dependence of this branch displays a softening with a minimum near the magneto-structural transition of T$_{S}$ $\sim$ 70 K and a recovery within the magnetically ordered low temperature phase. Soft acoustic instabilities are present in the collinear phases of the chalcogenides Fe$_{1+x}$Te where nematic order found in Fe$_{1+\delta}$Se is absent. We speculate, based on localized single-ion magnetism, that the relative energy scale of magnetic spin-orbital coupling on the Fe$^{2+}$ transition metal ion is important for the presence of a nematicity in the chalcogenides., Comment: (13 pages, 10 figures, to be published in Physical Review B)