ModRED : A Modular Self-Reconfigurable Robot for Autonomous Exploration

1. ModRED: A Modular Self-Reconfigurable Robot for Autonomous Exploration Carl Nelson*, Khoa Chu*, Prithviraj (Raj) Dasgupta**, Zachary Ramaekers** University of Nebraska *: Mechanical Engineering, University of Nebraska, Lincoln **: Computer Science, University of Nebraska, Omaha

2. 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

3. 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

4. Existing MSRs • Focusing on chain-type (as opposed to lattice-type) • Desire light, small package with high task adaptability and dexterity

5. Design Motivation

6. 4-DOF Architecture

7. Kinematics • Toroidal positionworkspace of onemodule end w.r.t.the other • Some embedded orientation workspace

8. Transmission • 2 motors • Solenoids (dis)engage DOF

9. 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)

10. Prototype System

11. 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

12. 2-module Inchworm Gait Pattern The series of steps that have to be done by 2 modules of ModRED: • 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

13. 2-module Inchworm Gait Pattern: Simulated on Webots Currently the gaits of ModRED are configured by hand

14. 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?

15. 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

16. Multi-robot Team Formation with Fixed Size Teams

17. Coverage with Multi-robot Teams Square Corridor • 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 Office

18. Dynamic Reconfigurations in ModRED • Having chains of modules is efficient for exploration • Having large chains of modules doing frequent reformationsis 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

19. 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)

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

21. 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

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

23. Thank You! For more information: Dr. Nelson’s lab at UNL: http://robots.unl.edu/Nelson/www/index.htm Dr. Dasgupta’s lab at UNO: http://cmantic.unomaha.edu Ke Cheng, UNO