SUPERBOT: A Deployable, Multi-Functional, and Modular Self-Reconfigurable Robotic System

Abstract – Self-reconfigurable robots are modular robots that can autonomously change their shape and size to meet specific operational demands. Recently, there has been a great interest in using self-reconfigurable robots in applications such as reconnaissance, rescue missions, and space applications. Designing and controlling self-reconfigurable robots is a difficult task. Hence, the research has primarily been focused on developing systems that can function in a controlled environment. This paper presents a novel self-reconfigurable robotic system called SuperBot, which addresses the challenges of building and controlling deployable self-reconfigurable robots. Six prototype modules have been built and preliminary experimental results demonstrate that SuperBot is a flexible and powerful system that can be used in challenging realworld applications

Systematic strategies for 3-dimensional modular robots

Modular robots have been studied an classified from different perspectives, generally focusing on the mechatronics. But the geometric attributes and constraints are the ones that determine the self-reconfiguration strategies. In two dimensions, robots can be geometrically classified by the grid in which their units are arranged and the free cells required to move a unit to an edge-adjacent or vertex-adjacent cell. Since a similar analysis does not exist in three dimensions, we present here a systematic study of the geometric aspects of three-dimensional modular robots. We find relations among the different designs but there are no general models, except from the pivoting cube one, that lead to deterministic reconfiguration plans. In general the motion capabilities of a single module are very limited and its motion constraints are not simple. A widely used method for reducing the complexity and improving the speed of reconfiguration plans is the use of meta-modules. We present a robust and compact meta-module of M-TRAN and other similar robots that is able to perform the expand/contract operations of the Telecube units, for which efficient reconfiguration is possible. Our meta-modules also perform the scrunch/relax and transfer operations of Telecube meta-modules required by the known reconfiguration algorithms. These reduction proofs make it possible to apply efficient geometric reconfiguration algorithms to this type of robots

A study of a novel modular variable geometry frame arranged as a robotic surface

The novel concept of a variable geometry frame is introduced and explored through a three-dimensional robotic surface which is devised and implemented using triangular modules. The link design is optimized using surplus motor dimensions as firm constraints, and round numbers for further arbitrary constraints. Each module is connected by a passive six-bar mechanism that mimics the constraints of a spherical joint at each triangle intersection. A three dimensional inkjet printer is used to create a six-module prototype designed around surplus stepper motors powered by an old computer power supply as a proof-of-concept example. The finite element method is applied to the static and dynamic loading of this device using linear three dimensional (6 degrees of freedom per node) beam elements to calculate the cartesian displacement and force and the angular displacement and torque at each joint. In this way, the traditional methods of finding joint forces and torques are completely bypassed. An efficient algorithm is developed to linearly combine local stiffness matrices into a full structural stiffness matrix for the easy application of loads. This is then decomposed back into the local matrices to easily obtain joint variables used in the design and open-loop control of the surface. Arbitrary equation driven surfaces are approximated ensuring that they are within the joints limits. Moving shapes are then calculated by considering the initial position of the surface, the desired position of the surface, and intermediate shapes at discrete times along the desired path. There are no sensors on the prototype, but feedback models and state estimators are developed for future use. These models include shape sampling methods derived from existing meshing algorithms, trajectory planning using sinusoidal acceleration profiles, spline-based path approximation to allow lower curvature paths able to be traversed more quickly and/or able to be travelled with a constant velocity and optimized by iteratively calculating actuator saturation with no discontinuities, and the optimal tracking of a desired path (modeled with a time-varying ricatti equation)

Dynamic Reconfiguration in Modular Self-Reconfigurable Robots Using Multi-Agent Coalition Games

In this thesis, we consider the problem of autonomous self-reconfiguration by modular self-reconfigurable robots (MSRs). MSRs are composed of small units or modules that can be dynamically configured to form different structures, such as a lattice or a chain. The main problem in maneuvering MSRs is to enable them to autonomously reconfigure their structure depending on the operational conditions in the environment. We first discuss limitations of previous approaches to solve the MSR self-reconfiguration problem. We will then present a novel framework that uses a layered architecture comprising a conventional gait table-based maneuver to move the robot in a fixed configuration, but using a more complex coalition game-based technique for autonomously reconfiguring the robot. We discuss the complexity of solving the reconfiguration problem within the coalition game-based framework and propose a stochastic planning and pruning based approach to solve the coalition-game based MSR reconfiguration problem. We tested our MSR self-reconfiguration algorithm using an accurately simulated model of an MSR called ModRED (Modular Robot for Exploration and Discovery) within the Webots robot simulator. Our results show that using our coalition formation algorithm, MSRs are able to reconfigure efficiently after encountering an obstacle. The average “reward” or efficiency obtained by an MSR also improves by 2-10% while using our coalition formation algorithm as compared to a previously existing multi-agent coalition formation algorithm. To the best of our knowledge, this work represents two novel contributions in the field of modular robots. First, ours is one of the first research techniques that has combined principles from human team formation techniques from the area of computational economics with dynamic self-reconfiguration in modular self-reconfigurable robots. Secondly, the modeling of uncertainty in coalition games using Markov Decision Processes is a novel and previously unexplored problem in the area of coalition formation. Overall, this thesis addresses a challenging research problem at the intersection of artificial intelligence, game theory and robotics and opens up several new directions for further research to improve the control and reconfiguration of modular robots

Optimal self assembly of modular manipulators with active and passive modules

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 89-92).In this thesis, we describe algorithms to build self-assembling robot systems composed of active modular robots and passive bars. The robotic module is the Shady3D robot and the passive component is a rigid bar with embedded IR LEDs. We propose algorithms that demonstrate the cooperative aggregation of modular robotic manipulators with greater capability and workspace out of these two types of elements. The distributed algorithms are based on locally optimal matching. We demonstrate how to build an active structure by the cooperative aggregation and disassembly of modular robotic manipulators. A target structure is modeled as a dynamic graph. We prove that the same optimality - quadratic competitive ratio - as for the static graph can be achieved for the algorithms. We demonstrate how this algorithm can be used to build truss-like structures. We present results from physical experiments in which two 3DOF Shady3D robots and one rigid bar coordinate to self-assemble into a 6DOF manipulator. We then demonstrate cooperative algorithms for forward and inverse kinematics, grasping, and mobility with this arm.by Seung-kook Yun.S.M

Motion Planning for Variable Topology Trusses: Reconfiguration and Locomotion

Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by not only controlling joint positions as with fixed morphology robots, but also reconfiguring the connectivity between truss members in order to change their topology. The motion planning problem for VTT robots is difficult due to their varying morphology, high dimensionality, the high likelihood for self-collision, and complex motion constraints. In this paper, a new motion planning framework to dramatically alter the structure of a VTT is presented. It can also be used to solve locomotion tasks that are much more efficient compared with previous work. Several test scenarios are used to show its effectiveness. Supplementary materials are available at https://www.modlabupenn.org/vtt-motion-planning/.Comment: 20 pages, 36 figure

Challenges in the Locomotion of Self-Reconfigurable Modular Robots

Self-Reconfigurable Modular Robots (SRMRs) are assemblies of autonomous robotic units, referred to as modules, joined together using active connection mechanisms. By changing the connectivity of these modules, SRMRs are able to deliberately change their own shape in order to adapt to new environmental circumstances. One of the main motivations for the development of SRMRs is that conventional robots are limited in their capabilities by their morphology. The promise of the field of self-reconfigurable modular robotics is to design robots that are robust, self-healing, versatile, multi-purpose, and inexpensive. Despite significant efforts by numerous research groups worldwide, the potential advantages of SRMRs have yet to be realized. A high number of degrees of freedom and connectors make SRMRs more versatile, but also more complex both in terms of mechanical design and control algorithms. Scalability issues affect these robots in terms of hardware, low-level control, and high-level planning. In this thesis we identify and target three major challenges: (i) Hardware design; (ii) Planning and control; and, (iii) Application challenges. To tackle the hardware challenges we redesigned and manufactured the Self-Reconfigurable Modular Robot Roombots to meet desired requirements and characteristics. We explored in detail and improved two major mechanical components of an SRMR: the actuation and the connection mechanisms. We also analyzed the use of compliant extensions to increase locomotion performance in terms of locomotion speed and power consumption. We contributed to the control challenge by developing new methods that allow an arbitrary SRMR structure to learn to locomote in an efficient way. We defined a novel bio-inspired locomotion-learning framework that allows the quick and reliable optimization of new gaits after a morphological change due to self-reconfiguration or human construction. In order to find new suitable application scenarios for SRMRs we envision the use of Roombots modules to create Self-Reconfigurable Robotic Furniture. As a first step towards this vision, we explored the use and control of Plug-n-Play Robotic Elements that can augment existing pieces of furniture and create new functionalities in a household to improve quality of life

Modular Robots Morphology Transformation And Task Execution

Self-reconfigurable modular robots are composed of a small set of modules with uniform docking interfaces. Different from conventional robots that are custom-built and optimized for specific tasks, modular robots are able to adapt to many different activities and handle hardware and software failures by rearranging their components. This reconfiguration capability allows these systems to exist in a variety of morphologies, and the introduced flexibility enables self-reconfigurable modular robots to handle a much wider range of tasks, but also complicates the design, control, and planning. This thesis considers a hierarchy framework to deploy modular robots in the real world: the robot first identifies its current morphology, then reconfigures itself into a new morphology if needed, and finally executes either manipulation or locomotion tasks. A reliable system architecture is necessary to handle a large number of modules. The number of possible morphologies constructed by modules increases exponentially as the number of modules grows, and these morphologies usually have many degrees of freedom with complex constraints. In this thesis, hardware platforms and several control methods and planning algorithms are developed to build this hierarchy framework leading to the system-level deployment of modular robots, including a hybrid modular robot (SMORES-EP) and a modular truss robot (VTT). Graph representations of modular robots are introduced as well as several algorithms for morphology identification. Efficient mobile-stylereconfiguration strategies are explored for hybrid modular robots, and a real-time planner based on optimal control is developed to perform dexterous manipulation tasks. For modular truss robots, configuration space is studied and a hybrid planning framework (sampling-based and search-based) is presented to handle reconfiguration activities. A non-impact rolling locomotion planner is then developed to drive an arbitrary truss robot in an environment

Coordinating construction by a distributed multi-robot system

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 147-156).This thesis presents a decentralized algorithm for the coordinated assembly of 3D objects that consist of multiple types of parts, using a networked team of robots. We describe the algorithm and analyze its stability and adaptation properties. We partition construction in two tasks, tool delivery and assembly. Each task is performed by a networked team of specialized robots. We analyze the performance of the algorithms using the balls into bins problem, and show their adaptation to failure of robots, dynamic constraints, multiple types of elements and reconfiguration. We instantiate the algorithm to building truss-like objects using rods and connectors. The algorithm has been implemented in simulation and results for constructing 2D and 3D parts are shown. Finally, we describe hardware implementation of the algorithms where mobile manipulators assemble smarts parts with IR beacons.by Seung-kook Yun.Ph.D