Tarik Tosun

Automated Self-Assembly of Large Maritime Structures by a Team of Robotic Boats

We present the methodology, algorithms, system design, and experiments addressing the self-assembly of large teams of autonomous robotic boats into floating platforms. Identical self-propelled robotic boats autonomously dock together and form connected structures with controllable variable stiffness. These structures can self-reconfigure into arbitrary shapes limited only by the number of rectangular elements assembled in brick-like patterns. An O(m2) complexity algorithm automatically generates assembly plans which maximize opportunities for parallelism while constructing operator-specified target configurations with m components. The system further features an O(n3) complexity algorithm for the concurrent assignment and planning of trajectories from n free robots to the growing structure. Such peer-to-peer assembly among modular robots compares favorably to a single active element assembling passive components in terms of both construction rate and potential robustness through redundancy. We describe hardware and software techniques to facilitate reliable docking of elements in the presence of estimation and actuation errors, and we consider how these local variable stiffness connections may be used to control the structural properties of the larger assembly. Assembly experiments validate these ideas in a fleet of 0.5 m long modular robotic boats with onboard thrusters, active connectors, and embedded computers.

Self-assembly of a swarm of autonomous boats into floating structures

This paper addresses the self-assembly of a large team of autonomous boats into floating platforms. We describe the design of individual boats, the systems concept, the algorithms, the software architecture and experimental results with prototypes that are 1:12 scale realizations of modified ISO shipping containers, with the goal of demonstrating self-assembly into large maritime structures such as air strips, bridges, harbors or sea bases. Each container is a robotic module capable of holonomic motion that can dock in a brick pattern to form arbitrary shapes. Over 60 modules were built of varying capability. The docking mechanism is designed to be robust to large disturbances that can be expected in the high seas. The docking mechanism also incorporates adjustable stiffness so that the conglomerate can comply to waves representative of sea state three, and have the ability to dynamically stiffen as required. The component modules for autonomous assembly, docking and simultaneous collision-free planning as well as the software architecture are presented along with the description of experimental verification.

A General Method for Kinematic Retargeting: Adapting Poses Between Humans and Robots

This paper presents a method for kinematic retargeting that is general to a broad class of kinematic chains. Kinematic retargeting is the adaptation of a pose or motion from one kinematic embodiment to another. Our method distinguishes itself in its ability to adapt poses to new robots with very little configuration by the user. We accomplish this by defining two general metrics for retargeting and minimizing a cost function which is the weighted sum of these two metrics. This allows the method to automatically adapt poses between source and target chains that have different link lengths and degrees of freedom.These capabilities address a specific problem in Human-Robot Interaction (HRI), where behaviors are often defined in a robot-specific manner. The ability to automatically adapt behaviors from humans to new robots, and from one robot to another, will facilitate experimental repeatability. Through simulation and experiments, we demonstrate that our method is effective in adapting poses across chains with different numbers of joints, and in adapting socially expressive gestures from a human to two very different robots.Copyright

Design and characterization of the EP-Face connector

We present the EP-Face connector, a novel connector for hybrid chain-lattice type modular robots that is highstrength (88.4N), compact, fast, power efficient, and robust to position errors. The connector consists of an array of electro-permanent magnets (EP magnets) embedded in a planar face. EP magnets are solid-state magnets that can be turned on and off and require power only when changing state. In this paper, we present the design of the connector, manufacturing process, detailed experimental characterization of the connector strength under different loading conditions, and compare its performance to existing magnetic and mechanical connectors. We also illustrate the functional benefits of the EPFace by demonstrating reconfiguration with the SMORES-EP robot.

Computer-Aided Compositional Design and Verification for Modular Robots

To take full advantage of the flexibility of a modular robot system, users must be able to create and verify new configurations and behaviors quickly. We present a design framework that facilitates rapid creation of new configurations and behaviors through composition of existing ones, and tools to verify configurations and behaviors as they are being created. New configurations are created by combining existing sub-configurations, for example combining four legs and a body to create a walking robot. Behaviors are associated with each configuration, so that when sub-configurations are composed, their associated behaviors are immediately available for composition as well. We introduce a new motion description language (Series-Parallel Action Graphs) that facilitates the rapid creation of complex behaviors by composition of simpler behaviors. We provide tools that automatically verify configurations and behaviors during the design process, allowing the user to identify problems early and iterate quickly. In addition to verification, users can evaluate their configurations and behaviors in a physics-based simulator.

On embeddability of modular robot designs

We address the problem of detecting embeddability of modular robots: namely, to decide automatically whether a given modular robot design can simulate the functionality of a seemingly different design. To that end, we introduce a novel graph representation for modular robots and formalize the notion of embedding through topological and kinematic conditions. Based on that, we develop an algorithm that decides embeddability when the two involved designs have tree topologies. Our algorithm performs two passes and involves dynamic programming and maximum cardinality matching. We demonstrate our approach on real modular robots and show that we can detect embeddability of complex designs efficiently.

Accomplishing high-level tasks with modular robots

The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) a high-level mission planner, (2) a large design library spanning a wide set of functionality, (3) a design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by Jing et al. (in: Robotics: science and systems, 2016), extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system.

PaintPots: Low cost, accurate, highly customizable potentiometers for position sensing

The PaintPot manufacturing process is a new way to create low-cost, low-profile, highly customizable potentiometers for position sensing in robotic applications. It uses widely accessible materials, requires no special expertise, and creates custom potentiometers in a variety of shapes and sizes, including curved surfaces. PaintPots offer accuracy and precision performance comparable with commercial (non-customizable) options through a calibration process that trades small computation for cost. This paper includes detailed PaintPot manufacturing and calibration processes, and experiments that validate the accuracy, precision, and lifetime performance of PaintPots, comparable to commercial sensors. We also provide a case-study application in the SMORES-EP modular robot, and show how the PaintPot process can be used to create resistive surfaces capable of sensing position in 2D on planes and spheres.

An End-to-End System for Accomplishing Tasks with Modular Robots: Perspectives for the AI community

The advantage of modular robot systems lies in their flexibility, but this advantage can only be realized if there exists some reliable, effective way of generating configurations (shapes) and behaviors (controlling programs) appropriate for a given task. In this paper, we present an end-to-end system for addressing tasks with modular robots, and demonstrate that it is capable of accomplishing challenging multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) A high-level mission planner, (2) A large design library spanning a wide set of functionality, (3) A design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. The broader goal of this project is enabling users to address real-world tasks using modular robots. We believe this work represents an important step toward this larger goal.