15 accepted papers
Direct laser deposition, a specialized form of additive manufacturing, shows good potential in numerous high-value applications such as the repair of aeroengine blades. However, the traditional setup for this technique is bulky and not suited for in-situ repair, requiring the costly disassembly of t…
Robotic hands, prosthetics, and hand exoskeletons struggle with replicating the natural dexterity of human hands: the mechanical intelligence of our muscles can be hardly replicated with rigid actuators, while soft mechanisms compromise precision. Underactuated hand mechanisms represent a trade-off …
Thoracostomy involves draining fluid from the pleural cavity using chest tubes. This medical intervention is currently performed manually by inserting a hollow flexible tube, risking damage to vital organs, including the lungs, diaphragm, spleen, and mediastinum, due to the lack of control over the …
Consider the problem of finding the best matching in a weighted graph where we only have access to predictions of the actual stochastic weights, based on an underlying context. If the predictor is the Bayes optimal one, then computing the best matching based on the predicted weights is optimal. Howe…
Terminal embeddings have emerged as a powerful tool for dimension reduction. Given a set of points $P\subset \mathbb{R}^d$, a terminal embedding is a mapping $f:\mathbb{R}^d\rightarrow \mathbb{R}^t$ that preserves the pairwise distance between any pair of points $p\in P$ and $q\in \mathbb{R}^d$ up t…
Direct laser deposition, a form of additive manufacturing, shows potential in numerous high-value applications such as aeroengine blade repair. However, conventional setups are bulky and unsuitable for in-situ repair, requiring costly engine disassembly. This letter presents a miniaturized high-repe
Thoracostomy involves draining fluid from the pleural cavity using chest tubes. This medical intervention is currently performed manually by inserting a hollow flexible tube, risking damage to vital organs, including the lungs, diaphragm, spleen, and mediastinum, due to the lack of control over the
In the random-order model for online learning, the sequence of losses is chosen upfront by an adversary and presented to the learner after a random permutation. Any random-order input is *asymptotically* equivalent to a stochastic i.i.d.~one, but, for finite times, it may exhibit significant *non-st…
We study the sublinear multivariate mean estimation problem in $d$-dimensional Euclidean space. Specifically, we aim to find the mean $\mu$ of a ground point set $A$, which minimizes the sum of squared Euclidean distances of the points in $A$ to $\mu$. We first show that a multiplicative $(1+\vareps…
Motivated by recent work in computational social choice, we extend the metric distortion framework to clustering problems. Given a set of n agents located in an underlying metric space, our goal is to partition them into k clusters, optimizing some social cost objective. The metric space is defined…
In online learning, a decision maker repeatedly selects one of a set of actions, with the goal of minimizing the overall loss incurred. Following the recent line of research on algorithms endowed with additional predictive features, we revisit this problem by allowing the decision maker to acquire a…
Continuum robots are flexible mechanisms that enable tasks in cluttered environments where conventional robots cannot operate. However, their few design parameters and task/manufacturing constraints leave small margins for optimization. In this paper, we expand the design space of continuum robots b
We study fully dynamic online selection problems in an adversarial/stochastic setting that includes Bayesian online selection, prophet inequalities, posted price mechanisms, and stochastic probing problems subject to combinatorial constraints. In the classical ``incremental'' version of the proble…
Continuum robots are able of in-situ inspection tasks in cluttered environments and narrow passages, where conventional robots and human operators cannot intervene. However, such intervention often requires the robot to interact with the environment, and the low stiffness and payload of continuum ro
Efficient path planning for hyper-redundant continuum and snake-like robots is a challenging task due to limited sensing capabilities, high computational loads, multiple possible solutions, and non-linear models. This letter presents a new approach to snake robot navigation and coiling, with an algo