Carl Nelson*, Khoa Chu*, Prithviraj (Raj) Dasgupta**, Zachary Ramaekers** University of Nebraska *: Mechanical Engineering, University of Nebraska, Lincoln **: Computer Science, University of Nebraska, Omaha

Introduction Modular self-reconfigurable robots (MSRs) are robots consisting of identical programmable modules capable of reconfiguration. To enable long-term robotic support of space missions, MSRs needed for: unstructured environments changing tasks self-repair MSR capabilities can result in savings in: time money lives

Design Motivation Types of MSR Mobile – CEBOT & S-bot Chain – CONRO, Polypod, & PolyBot Lattice – Telecube, Molecule, & Stochastic Hybrid – Superbot & MTran II Advanced chain-type MSRs have up to three degrees of freedom (DOF) More tasks are possible with higher numbers of DOF

Existing MSRs Focusing on chain-type (as opposed to lattice- type) Desire light, small package with high task adaptability and dexterity SystemClassDOF Motion Space YaMorchain1 2-D Tetrobotchain1 3-D PolyBotchain1 3-D Molecubechain1 3-D CONROchain2 3-D Polypodchain2 3-D MTRAN IIhybrid2 3-D Superbothybrid3 3-D

Design Motivation

4-DOF Architecture

Kinematics Toroidal position workspace of one module end w.r.t. the other Some embedded orientation workspace

Transmission 2 motors Solenoids (dis)engage DOF

Reconfiguration and Locomotion Intended to handle unstructured environments Needs to be able to form useful configurations for task accomplishment as well as locomotion (multi-module or single-module)

Prototype System

Webots Robot Simulator: Simulated ModRED modules Accurate models for environments, robots Physics engine can be used to simulate external forces Simulations in real or accelerated time

2-module Inchworm Gait Pattern Step 1: Initial configuration Step 2a: Raise rear joint of posterior module Step 2b: Raise forward joint of anterior module Step 2c: Extend posterior module Step 3a: Lower connected section Step 3b: Raise posterior rear module and adjust angle Step4a: Lower posterior rear module Step 4b: Raise connected section Step 4c: Contract posterior module Step 4d: Extend anterior module Step 5a: Lower connected section Step 5b: Raise anterior front module and adjust angle Step 6a: Lower anterior front module Step 6b: Raise front joint of anterior module Step 7a: Contract front module Step 7b: Lower rear joint of posterior module Step 7c: Lower front joint of anterior module The series of steps that have to be done by 2 modules of ModRED:

2-module Inchworm Gait Pattern: Simulated on Webots Currently the gaits of ModRED are configured by hand

Research Challenges in Designing Autonomous MSRs To enable long-term robotic support of space missions, MSRs can encounter: unstructured environments changing tasks self-repair These require autonomous, dynamic reconfiguration among the modules Issues involved: What is the best module or set of modules to pair with? What is the best set of connections to have with neighboring modules?

Operational Issues and Robot Capabilities Distributed – no shared memory or map of the environment that the robots can use to know which portion of the environment is covered Each ModRED module is frugal...limited storage and computation capabilities Can’t store map of the entire environment Other challenges: Sensor and encoder noise, communication overhead, localizing robots Learn from our research on multi-robot team formation to get directions for investigating these issues

Multi-robot Team Formation with Fixed Size Teams

Coverage with Multi-robot Teams Square Corridor Office Larger robot team sizes in environments with many obstacles reduces the efficiey of exploration Lesson: Robot team sizes cannot remain fixed – must be adapted dynamically based on operation conditions

Dynamic Reconfigurations in ModRED Having chains of modules is efficient for exploration Having large chains of modules doing frequent reformations is inefficient for exploration Can we make the modules change their configurations dynamically Based on their recent performance: If a large chain is doing frequent reformations (and getting bad exploration efficiency), split the chain into smaller chain and see if exploration efficiency improves

Structured Way to Form Modules: Coalition Games Coalition games provide a theory to divide a set of players into smaller subsets or teams We have used a form of coalition games called weighted voting games (WVG)

Layered Approach 20 Weighted Voting Game Robot Controller Layer Mediator Works with agent utility, agent strategies, equilibrium points, etc. Works with physical characteristics such as wheel speed, sensor reading, pose, etc. Map from agent strategy to robot action, sensor reading to agent utility, maintain data structure for mapping

Ongoing and Future Work Further develop the prototype of ModRED Sensors, actuators, comms, processor Adapt the results from multi-robot team formation to chain robot formation using ModRED Terrain simulation Test hand-crafted and autonomous gait patterns Testing motion algorithms in variety of terrains on prototype ModRED

Acknowledgements We are grateful to NASA Nebraska Space Grant Consortium for their continued support in this project Students involved Zachary Ramaekers, UNO Khoa Chu, UNL Supervising Faculty Raj Dasgupta, Computer Science, UNO Carl Nelson, Mechanical Engineering, UNL/ Dept. of Surgery, UNMC

For more information: Dr. Nelson’s lab at UNL: Dr. Dasgupta’s lab at UNO: Ke Cheng, UNO23