Reconfiguring Non-Convex Holes in Pivoting Modular Cube Robots

We present an algorithm for self-reconfiguration of admissible 3D configurations of pivoting modular cube robots with holes of arbitrary shape and number. Cube modules move across the surface of configurations by pivoting about shared edges, enabling configurations to reshape themselves. Previous work provides a reconfiguration algorithm for admissible 3D configurations containing no non-convex holes; we improve upon this by handling arbitrary admissible 3D configurations. The key insight specifies a point in the deconstruction of layers enclosing non-convex holes at which we can pause and move inner modules out of the hole. We prove this happens early enough to maintain connectivity, but late enough to open enough room in the enclosing layer for modules to escape the hole. Our algorithm gives reconfiguration plans with O(n^2) moves for n modules

The single pixel GPS: learning big data signals from tiny coresets

We present algorithms for simplifying and clustering patterns from sensors such as GPS, LiDAR, and other devices that can produce high-dimensional signals. The algorithms are suitable for handling very large (e.g. terabytes) streaming data and can be run in parallel on networks or clouds. Applications include compression, denoising, activity recognition, road matching, and map generation. We encode these problems as (k, m)-segment mean problems. Formally, we provide (1 + ε)-approximations to the k-segment and (k, m)-segment mean of a d-dimensional discrete-time signal. The k-segment mean is a k-piecewise linear function that minimizes the regression distance to the signal. The (k,m)-segment mean has an additional constraint that the projection of the k segments on R[superscript d] consists of only m ≤ k segments. Existing algorithms for these problems take O(kn[superscript 2]) and n[superscript O(mk)] time respectively and O(kn[superscript 2]) space, where n is the length of the signal. Our main tool is a new coreset for discrete-time signals. The coreset is a smart compression of the input signal that allows computation of a (1 + ε)-approximation to the k-segment or (k,m)-segment mean in O(n log n) time for arbitrary constants ε,k, and m. We use coresets to obtain a parallel algorithm that scans the signal in one pass, using space and update time per point that is polynomial in log n. We provide empirical evaluations of the quality of our coreset and experimental results that show how our coreset boosts both inefficient optimal algorithms and existing heuristics. We demonstrate our results for extracting signals from GPS traces. However, the results are more general and applicable to other types of sensors.United States. Office of Naval Research (Grant ONR-MURI Award N00014-09-1-1051)United States. Office of Naval Research (Grant ONR-MURI Award N00014-09-1-1031)Singapore-MIT Alliance for Research and TechnologyGoogle (Firm

Data-driven task allocation for multi-robot deliveries

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 93-97).In this thesis, we present a distributed task allocation system for a team of robots serving queues of tasks in an environment. We consider how historical information about such a system's performance could be used to improve future allocations. Our model is representative of a multi-robot mail delivery service, in which teams of robots would have to cooperate to pick up and deliver packages in an environment. We provide a framework for task allocation, planning, and control of the system and analyze task switching as a method for improving a task allocation as the system is running. We first treat a system where robots exchange tasks as they encounter each other in the environment. We consider both cases where the number of robots matches the number of task queues being served and where it does not. Most importantly, for situations where an optimal task switching policy would be too computationally expensive, we provide heuristics that nonetheless guarantee task completion. Our simulations show that our heuristics also generally lower the costs of task completion. We incorporate historical data about system performance by looking at a spatial allocation of tasks to robots in the system. We propose an algorithm for partitioning the environment into regions of equal workload for the robots. In order to overcome communication constraints, we introduce hubs, locations where robots can pass tasks to each other. We simulate the system with this additional infrastructure and compare its performance to that without hubs. We find that hubs can significantly improve performance when the task queues themselves follow some spatial structure.by Cynthia Rueyi Sung.S.M

Economic burden of adverse drug reactions and potential for pharmacogenomic testing in Singaporean adults.

Adverse drug reactions (ADRs) contribute to hospitalization but data on its economic burden is scant. Pre-emptive pharmacogenetic (PGx) testing can potentially reduce ADRs and its associated costs. The objectives of this study were to quantify the economic burden of ADRs and to estimate the breakeven cost of pre-emptive PGx testing in Singapore. We collected itemized costs for 1000 random non-elective hospitalizations of adults admitted to a tertiary-care general hospital in Singapore. The presence of ADRs at admission and their clinical characteristics were reported previously. The economic burden of ADRs was assessed from two perspectives: (1) Total cost and (2) incremental costs. The breakeven cost of PGx testing was estimated by dividing avoidable hospitalization costs for ADRs due to selected drugs by the number of patients taking those drugs. The total cost of 81 admissions caused by ADRs was US$570,404. Costs were significantly higher for bleeding/elevated international normalized ratio (US$9906 vs. US$2251, p = 6.58 × 10-3) compared to other ADRs, and for drugs acting on the blood coagulation system (US$9884 vs. US$2229, p = 4.41 × 10-3) compared to other drug classes. There were higher incremental laboratory costs due to ADRs causing or being present at admission. The estimated breakeven cost of a pre-emptive PGx test for patients taking warfarin, clopidogrel, chemotherapeutic and neuropsychiatric drugs was US$114 per patient. These results suggest that future studies designed to directly measure the clinical and cost impact of a pre-emptive genotyping program will help inform clinical practice and health policy decisions

iDiary: from GPS signals to a text-searchable diary

This paper describes a system that takes as input GPS data streams generated by users' phones and creates a searchable database of locations and activities. The system is called iDiary and turns large GPS signals collected from smartphones into textual descriptions of the trajectories. The system features a user interface similar to Google Search that allows users to type text queries on their activities (e.g., "Where did I buy books?") and receive textual answers based on their GPS signals. iDiary uses novel algorithms for semantic compression (known as coresets) and trajectory clustering of massive GPS signals in parallel to compute the critical locations of a user. Using an external database, we then map these locations to textual descriptions and activities so that we can apply text mining techniques on the resulting data (e.g. LSA or transportation mode recognition). We provide experimental results for both the system and algorithms and compare them to existing commercial and academic state-of-the-art. This is the first GPS system that enables text-searchable activities from GPS data.United States. Office of Naval Research (Grant ONR-MURI Award N00014-12-1-1000)Hon Hai/Foxconn International Holdings Ltd.Singapore-MIT Alliance for Research and Technology CenterSingapore. National Research FoundationUnited States. Dept. of Defense. National Defense Science & Engineering Graduate Fellowship Progra

Pouch Motors: Printable Soft Actuators Integrated with Computational Design

We propose pouch motors, a new family of printable soft actuators integrated with computational design. The pouch motor consists of one or more inflatable gas-tight bladders made of sheet materials. This printable actuator is designed and fabricated in a planar fashion. It allows both easy prototyping and mass fabrication of affordable robotic systems. We provide theoretical models of the actuators compared with the experimental data. The measured maximum stroke and tension of the linear pouch motor are up to 28% and 100 N, respectively. The measured maximum range of motion and torque of the angular pouch motor are up to 80° and 0.2 N, respectively. We also develop an algorithm that automatically generates the patterns of the pouches and their fluidic channels. A custom-built fabrication machine streamlines the automated process from design to fabrication. We demonstrate a computer-generated life-sized hand that can hold a foam ball and perform gestures with 12 pouch motors, which can be fabricated in 15 min.National Science Foundation (U.S.) (1240383)National Science Foundation (U.S.) (1138967)United States. Department of Defens

An Untethered Miniature Origami Robot that Self-folds, Walks, Swims, and Degrades

A miniature robotic device that can fold-up on the spot, accomplish tasks, and disappear by degradation into the environment promises a range of medical applications but has so far been a challenge in engineering. This work presents a sheet that can self-fold into a functional 3D robot, actuate immediately for untethered walking and swimming, and subsequently dissolve in liquid. The developed sheet weighs 0.31g, spans 1.7cm square in size, features a cubic neodymium magnet, and can be thermally activated to self-fold. Since the robot has asymmetric body balance along the sagittal axis, the robot can walk at a speed of 3.8 body-length/s being remotely controlled by an alternating external magnetic field. We further show that the robot is capable of conducting basic tasks and behaviors, including swimming, delivering/carrying blocks, climbing a slope, and digging. The developed models include an acetone-degradable version, which allows the entire robot’s body to vanish in a liquid. We thus experimentally demonstrate the complete life cycle of our robot: self-folding, actuation, and degrading.National Science Foundation (U.S.) (Grant 1240383)National Science Foundation (U.S.) (Grant 1138967)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Kinegami: Algorithmic Design of Compliant Kinematic Chains From Tubular Origami

Origami processes can generate both rigid and compliant structures from the same homogeneous sheet material. In this article, we advance the origami robotics literature by showing that it is possible to construct an arbitrary rigid kinematic chain with prescribed joint compliance from a single tubular sheet. Our “Kinegami” algorithm converts a Denavit–Hartenberg specification into a single-sheet crease pattern for an equivalent serial robot mechanism by composing origami modules from a catalogue. The algorithm arises from the key observation that tubular origami linkage design reduces to a Dubins path planning problem. The automatically generated structural connections and movable joints that realize the specified design can also be endowed with independent user-specified compliance. We apply the Kinegami algorithm to a number of common robot mechanisms and hand-fold their algorithmically generated single-sheet crease patterns into functioning kinematic chains. We believe this is the first completely automated end-to-end system for converting an abstract manipulator specification into a physically realizable origami design that requires no additional human input