SHAPE-SHIFTING ROBOT FORMS FROM MAGNETIC SWARM – YOUTUBE
Concept of 3-D Self-reconfigurable Mechanical System – Self-assembling Many-unit Structure
CONCEPTS OF 3-D SELF-RECONFIGURABLE MECHANICAL SYSTEM – SELF-ASSEMBLING MANY-UNIT STRUCTURE
Ckbot modular self assembly – YouTube
CKBOT MODULAR SELF ASSEMBLY
A disturbance is applied to a configuration of CkBot modules, causing them to break apart. The clusters of modules then find each other and reconfigure.
Reconfiguration Planning for Heterogeneous Self-Reconfiguring Robots
RECONFIGURATION PLANNING FOR HETEROGENEOUS SELF-RECONFIGURING ROBOTS
Abstract: Current research in self-reconfiguring robots focuses predominantly on systems of identical modules. However, allowing modules of varying types, with different sensors,
for example, is of practical interest. In this paper, we propose the development of an algorithmic basis for heterogeneous self-reconfiguring systems. We demonstrate algorithmic feasibility by presenting O(n2) time centralized and O(n3) time decentralized solutions to the reconfiguration problem for n non-identical modules. As our centralized time bound is equal to the best published
homogeneous solution, we argue that space, as opposed to time, is the critical resource in the reconfiguration problem. Our results encourage the development both of applications that use heterogeneous self-reconfiguration, and also heterogeneous hardware systems.
Modeling Lattice Modular Reconfigurable Systems with Space Groups
MODELING LATTICE MODULAR RECONFIGURABLE SYSTEMS WITH SPACE GROUPS
by Nicolas Brener, Faiz Ben Amar, Philippe Bidaud with Laboratoire de Robotique de Paris
Several modular systems have been developed, one can distinguish lattice systems [1], [2], [3], [4], [5], [6] and chain type
systems [7], [8]. A review on these systems can be found in [9]. Today there is no theoretical background for the kinematical
design of modular systems. To design a new module one must…
Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms
HORMONE-INSPIRED SELF-ORGANIZATION AND DISTRIBUTED CONTROL OF ROBOTIC SWARMS
Abstract: The control of robot swarming in a distributed manner is a difficult problem because global behaviors must emerge as a result of many local actions. This paper uses a bio-inspired control method called the Digital Hormone Model (DHM) to control the tasking and executing of robot swarms based on local communication, signal propagation, and stochastic reactions. The DHM model is probabilistic, dynamic, fault-tolerant, computationally efficient, and can be easily tasked to change global behavior. Different from most existing distributed control and learning mechanisms, DHM considers the topological structure of the organization, supports dynamic reconfiguration and self-organization, and requires no globally unique identifiers for individual robots. The paper describes the DHM and presents the experimental results on simulating biological observations in the forming of feathers, and simulating wireless communicated swarm behavior at a large scale for attacking target, forming sensor networks, self-repairing, and avoiding pitfalls in mission execution.
Hierarchical Motion Planning for Self-reconfigurable Modular Robots
HIERARCHICAL MOTION PLANNING FOR SELF-RECONFIGURABLE MODULAR ROBOTS
Abstract— Motion planning for a self-reconfigurable robot involves coordinating the movement and connectivity of each of its homogeneous modules. Reconfiguration occurs when the shape of the robot changes from some initial configuration to a target configuration. Finding an optimal solution to reconfiguration problems involves searching the space of possible robot configurations.
As this space grows exponentially with the number of modules, optimal planning becomes intractable. We propose a hierarchical planning approach that computes heuristic global reconfiguration strategies efficiently. Our approach consists of a base planner that computes an optimal solution for a few modules and a hierarchical planner that calls this base planner or reuses pre-computed plans at each level of the hierarchy to ultimately compute a global suboptimal solution. We present results from a prototype implementation of the method that efficiently plans for self-reconfigurable robots with several thousand modules. We also discuss tradeoffs and performance issues including scalability, heuristics and plan optimality.
Generic Decentralized Control for a Class of Self-Reconfigurable Robots
GENERIC DECENTRALIZED CONTROL FOR A CLASS SELF-RECONFIGURABLE ROBOTS
Abstract: Previous work on self-reconfiguring modular robots has concentrated primarily on hardware and reconfiguration we introduce a new type of generic locomotion algorithmfor self-reconfigurable robots. The algorithms presented here are inspired by cellular automata, using geometric rules to control module actions. The actuation model used is a general one, presuming that modules can generally move over the surface of a group of modules. These algorithms can then be instantiated on to a variety of particular systems. Correctness proofs of the rule sets are also given for the generic geometry, with the intent that this analysis can carry over to the instantiated algorithms to provide different systems with correct locomotion algorithms.