Enabling New Functionally Embedded Mechanical Systems Via Cutting, Folding, and 3D Printing

Traditional design tools and fabrication methods implicitly prevent mechanical engineers from encapsulating full functionalities such as mobility, transformation, sensing and actuation in the early design concept prototyping stage. Therefore, designers are forced to design, fabricate and assemble individual parts similar to conventional manufacturing, and iteratively create additional functionalities. This results in relatively high design iteration times and complex assembly strategies

Child-Robot Spatial Arrangement in a Learning by Teaching Activity

In this paper, we present an experiment in the context of a child-robot interaction where we study the influence of the child-robot spatial arrangement on the child’s focus of attention and the perception of the robot’s performance. In the “Co-Writer learning by teaching” activity, the child teaches a Nao robot how to handwrite. Usually only face-to-face spatial arrangements are tested in educational child robot interactions, but we explored two spatial conditions from Kendon’s F-formation, the side-by-side and the face-to-face formations in a within subject experiment. We estimated the gaze behavior of the child and their consistency in grading the robot with regard to the robot’s progress in writing. Even-though the demonstrations provided by children were not different between the two conditions (i.e. the robot’s learning didn’t differ), the results showed that in the side-by-side condition children tended to be more indulgent with the robot’s mistakes and to give it better feedback. These results highlight the influence of experimental choices in child-robot interaction

Enabling Parallel Wireless Communication in Mobile Robot Teams

Wireless inter-robot communication enables robot teams to cooperatively solve complex problems that cannot be addressed by a single robot. Applications for cooperative robot teams include search and rescue, exploration and surveillance. Communication is one of the most important components in future autonomous robot systems and is essential for core functions such as inter-robot coordination, neighbour discovery and cooperative control algorithms. In environments where communication infrastructure does not exist, decentralised multi-hop networks can be constructed using only the radios on-board each robot. These are known as wireless mesh networks (WMNs). However existing WMNs have limited capacity to support even small robot teams. There is a need for WMNs where links act like dedicated point-to-point connections such as in wired networks. Addressing this problem requires a fundamentally new approach to WMN construction and this thesis is the first comprehensive study in the multi-robot literature to address these challenges. In this thesis, we propose a new class of communication systems called zero mutual interference (ZMI) networks that are able to emulate the point-to-point properties of a wired network over a WMN implementation. We instantiate the ZMI network using a multi-radio multi-channel architecture that autonomously adapts its topology and channel allocations such that all network edges communicate at the full capacity of the radio hardware. We implement the ZMI network on a 100-radio testbed with up to 20-individual nodes and verify its theoretical properties. Mobile robot experiments also demonstrate these properties are practically achievable. The results are an encouraging indication that the ZMI network approach can facilitate the communication demands of large cooperative robot teams deployed in practical problems such as data pipe-lining, decentralised optimisation, decentralised data fusion and sensor networks

Evaluating Group-Robot Interaction in Crowded Public Spaces: A Week-Long Exploratory Study in the Wild with a Humanoid Robot Guiding Visitors Through a Science Museum

Postprint (published version

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

物理/バーチャル空間の接続と分離を媒介する可動壁に関する研究

Tohoku University博士（情報科学）thesi

ECO: Egocentric Cognitive Mapping

We present a new method to localize a camera within a previously unseen environment perceived from an egocentric point of view. Although this is, in general, an ill-posed problem, humans can effortlessly and efficiently determine their relative location and orientation and navigate into a previously unseen environments, e.g., finding a specific item in a new grocery store. To enable such a capability, we design a new egocentric representation, which we call ECO (Egocentric COgnitive map). ECO is biologically inspired, by the cognitive map that allows human navigation, and it encodes the surrounding visual semantics with respect to both distance and orientation. ECO possesses three main properties: (1) reconfigurability: complex semantics and geometry is captured via the synthesis of atomic visual representations (e.g., image patch); (2) robustness: the visual semantics are registered in a geometrically consistent way (e.g., aligning with respect to the gravity vector, frontalizing, and rescaling to canonical depth), thus enabling us to learn meaningful atomic representations; (3) adaptability: a domain adaptation framework is designed to generalize the learned representation without manual calibration. As a proof-of-concept, we use ECO to localize a camera within real-world scenes---various grocery stores---and demonstrate performance improvements when compared to existing semantic localization approaches