Melinda Malley, Michael Rubenstein, and Radhika Nagpal. 2017. “
Flippy: A Soft, Autonomous Climber with Simple Sensing and Control.” In IEEE/RSJ Intl Conference on Intelligent Robots and Systems (IROS).
Abstract
Climbing robots have many potential applications including maintenance, monitoring, search and rescue, and self-assembly. While numerous climbing designs have been investigated, most are limited to stiff components. Flippy (Fig. 1) is a small, flipping biped robot with a soft, flexible body and on-board power and control. Due to its built-in compliance, flipping gait, and corkscrew gripper, it can autonomously climb up and down surfaces held at any angle relative to gravity and transition from one surface to another, without complex sensing or control. In this paper, we demonstrate the robot’s ability to flip consistently over a flat Velcro surface and 2D Velcro track, where it reliably climbs vertically, upside down and back to a flat surface, completing all the interior transitions in-between.
iros2017-malley.pdf Florian Berlinger, Jeff Dusek, Melvin Gauci, and Radhika Nagpal. 2017. “
Robust Maneuverability of a Miniature Low-Cost Underwater Robot using Multiple Fin Actuation.” IEEE Robotics and Automation Letters (RA-L), PP, 99.
Abstract
In this paper we present the design of a miniature (100 mm) autonomous underwater robot that is low-cost ($ 100), easy to manufacture, and highly maneuverable. A key aspect of the robot design that makes this possible is the use of low-cost magnet-in-coil actuators, which have a small profile and minimal sealing requirements. This allows us to create a robot with multiple flapping fin propulsors that independently control robot motions in surge, heave, and yaw. We present several results on the robot, including: (i) quantified open-loop swimming characteristics; (ii) autonomous behaviors using a pressure sensor and an IMU to achieve controlled swimming of prescribed trajectories; (iii) feedback from an optic sensor to enable homing to a light source. The robot is designed to form the basis for underwater swarm robotics testbeds, where low cost and ease of manufacture are critical, and 3D maneuverability allows testing complex coordination inspired by natural fish schools. Individually, miniature and low-cost underwater robots can also provide a platform for the study of 3D autonomy and marine vehicle dynamics in educational and resource-constrained settings.
ral2017-berlinger.pdf Kirstin Petersen and Radhika Nagpal. 2017. “
Complex Design by Simple Robots: A Collective Embodied Intelligence Approach to Construction.” Architectural Design, Special Issue: Autonomous Assembly: Designing for a New Era of Collective Construction, 87, 4, Pp. 44-49.
AbstractNature's builders – from termites to beavers – offer a model of collective intelligence that can inspire robotic construction. Kirstin Petersen, Assistant Professor in Electrical and Computer Engineering at Cornell University, Ithaca, New York, and Radhika Nagpal, Professor in Computer Science at the Harvard School of Engineering and Applied Sciences, Cambridge, Massachusetts, describe several recent projects in this field that they have been involved in, both separately and collaboratively.
Tsvetomira (Mira) Radeva, Anna Dornhaus, Nancy Lynch, Radhika Nagpal, and Hsin-Hao Su. 2017. “
Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems.” PLoS computational biology, 13, 12.
Publisher's Version (open-access)Abstract(Author summary)
Many complex systems have to allocate their units to different functions: cells in an embryo develop into different tissues, servers in a computer cluster perform different cal- culations, and insect workers choose particular tasks, such as brood care or foraging. Here we demonstrate that this process does not automatically become easier or harder with sys- tem size. If more workers are present than needed to complete the work available, some workers will always be idle; despite this, having surplus workers makes redistributing them across the tasks that need work much faster. Thus, unexpectedly, such surplus, idle workers may potentially significantly improve system performance. Our work suggests that interdisciplinary studies between biology and distributed computing can yield novel insights for both fields.
Melvin Gauci, Monica Ortiz, Michael Rubenstein, and Radhika Nagpal. 2017. “
Error Cascades in Collective Behavior: A Case Study of the Gradient Algorithm on 1000 Physical Agents.” In 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
Abstract
The gradient, or hop count, algorithm is inspired by nat- ural phenomena such as the morphogen gradients present in multi-cellular development. It has several applications in multi-agent systems and sensor networks, serving as a basis for self-organized coordinate system formation, and finding shortest paths for message passing. It is a simple and well- understood algorithm in theory. However, we show here that in practice, it is highly sensitive to specific rare errors that emerge at larger scales. We implement it on a system of 1000 physical agents (Kilobot robots) that communicate asynchronously via a noisy wireless channel. We observe that spontaneous, short-lasting rare errors made by a sin- gle agent (e.g. due to message corruption) propagate spa- tially and temporally, causing cascades that severely hinder the algorithm’s functionality. We develop a mathematical model for temporal error propagation and validate it with experiments on 100 agents. This work shows how multi- agent algorithms that are believed to be simple and robust from theoretical insight may be highly challenging to im- plement on physical systems. Systematically understanding and quantifying their current limitations is a first step in the direction of improving their robustness for implementation.
aamas2017-gauci.pdf Ben Green, Paul Bardunias, J. Scott Turner, Radhika Nagpal, and Justin Werfel. 2017. “
Excavation and aggregation as organizing factors in de novo construction by mound-building termites.” Proceedings of the Royal Society B, 284, 1856.
Publisher's VersionAbstractTermites construct complex mounds that are orders of magnitude larger than any individual and fulfil a variety of functional roles. Yet the processes through which these mounds are built, and by which the insects organize their efforts, remain poorly understood. The traditional understanding focuses on stigmergy, a form of indirect communication in which actions that change the environment provide cues that influence future work. Termite construction has long been thought to be organized via a putative ‘cement pheromone’: a chemical added to deposited soil that stimulates further deposition in the same area, thus creating a positive feedback loop whereby coherent structures are built up. To investigate the detailed mechanisms and behaviours through which termites self-organize the early stages of mound construction, we tracked the motion and behaviour of major workers from two Macrotermes species in experimental arenas. Rather than a construction process focused on accumulation of depositions, as modelsbased on cement pheromone would suggest, our results indicated that the primary organizing mechanisms were based on excavation. Digging activity was focused on a small number of excavation sites, which in turn provided templates for soil deposition. This behaviour was mediated by a mechanism of aggregation, with termites being more likely to join in the work at an excavation site as the number of termites presently working at that site increased. Statistical analyses showed that this aggregation mechanism was a response to active digging, distinct from and unrelated to putative chemical cues that stimulate deposition. Agent-based simulations quantitatively supported the interpretation that the early stage of de novo construction is primarily organized by excavation and aggregation activity rather than by stigmergic deposition.
Nicole Carey, Radhika Nagpal, and Justin Werfel. 2017. “
Fast, accurate, small-scale 3D scene capture using a low-cost depth sensor.” In IEEE Winter Conference on Applications of Computer Vision (WACV).
Abstract
Commercially available depth sensing devices are pri- marily designed for domains that are either macroscopic, or static. We develop a solution for fast microscale 3D re- construction, using off-the-shelf components. By the addi- tion of lenses, precise calibration of camera internals and positioning, and development of bespoke software, we turn an infrared depth sensor designed for human-scale motion and object detection into a device with mm-level accuracy capable of recording at up to 30Hz.
wacv17-carey.pdf Elizabeth E. Esterley, Helen McCreery, and Radhika Nagpal. 2017. “
Models of Adaptive Navigation, Inspired by Ant Cooperative Transport in the Presence of Obstacles.” In IEEE Artificial Life Conference (ALIFE).
Abstract
Cooperative transport is an impressive example of collective behavior in ants, where groups of ants work together to move heavy food objects back to their nest over heterogeneous terrain. This behavior also serves as a model for bio-inspired robotics. While many studies have considered the mechanisms by which ants transport objects in simple settings, few have looked at how they deal with obstacles and heterogeneous terrain. A recent study on Paratrechina longicornis (crazy ants) demonstrated that groups of these ants implement a stochastic, adaptive, and robust cooperative transport strategy that allows them to succeed at navigating challenging obstacles that require moving away from their goal. In this paper, we use group-level computational models to investigate the significance and implications of this biological strategy. We develop an algorithm that reproduces important elements of the strategy, and compare it to several benchmark algorithms for a range of obstacle sizes and shapes. Our results show that, for smaller obstacles, the ant-inspired adaptive stochastic strategy is adept at efficient navigation, due to its ability to match the level of randomness it uses to unknown object size and shape. We also find some unexpected differences between our results and the original ant transport behavior, suggesting new biological experiments.
alife2017-esterly.pdf(Best Student Paper, special commendation)
Serena Booth, James Tompkins, Hanspeter Pfister, Jim Waldo, Krzysztof Gajos, and Radhika Nagpal. 2017. “
Piggybacking Robots: Human-Robot Overtrust in University Dormitory Security.” In ACM/IEEE International Conference on Human-Robot Interaction (HRI).
(pdf)Abstract
Can overtrust in robots compromise physical security? We posi- tioned a robot outside a secure-access student dormitory and made it ask passersby for access. Individual participants were as likely to assist the robot in exiting the dormitory (40% assistance rate, 4/10 individuals) as in entering (19%, 3/16 individuals). Groups of people were more likely than individuals to assist the robot in entering (71%, 10/14 groups). When the robot was disguised as a food delivery agent for the ctional start-up Robot Grub, individ- uals were more likely to assist the robot in entering (76%, 16/21 individuals). Lastly, participants who identied the robot as a bomb threat demonstrated a trend toward assisting the robot (87%, 7/8 individuals, 6/7 groups). us, overtrust—the unfounded belief that the robot does not intend to deceive or carry risk—can represent a signicant threat to physical security at a university dormitory.
(based on senior thesis, awarded Harvard Hoopes Prize)