September 28, Course Projects
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September 28, Course Projects



Multi-Robot Systems

Multi-Robot Systems



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September 28, Course Projects September 28, Course Projects Presentation Transcript

  • Multi-Robot Systems
    CSCI 7000-006
    Monday, September 28, 2009
  • Crafting a Research Project
    What is “research”?
    Preliminary requirement: open question
    Secondary: how to solve it
    Hypothesis: states question and leads to methodology
    Sources of confusion
    You need to investigate what the questions are
    You need to design your experiment
    You need to optimize your system
    You need to develop tools to investigate
  • Collaborative Lifting
    Problem: Lifting a box collaboratively
    Hypothesis: Problem can be encoded in a single cost function that allows gradient-based control
    Method: formal stability analysis
    Gregory Brown
  • Collaborative Bouncing
    Problem: Bouncing a ball back and forth between two robots
    Hypothesis: Use a particle-filter for predicting system dynamics
    Method: Dynamical model and implementation
    Mikael Ian Pryor
  • Probabilistic Patrolling
    Problem: Patrol an environment efficiently but unpredictable to the adversary
    Hypothesis: Use a balance between exploration and exploitation during coverage
    Method: Probabilistic algorithm, model, implementation
  • Probabilistic Localization with Geometric Constraints
    Problem: Localizing “intelligent” objects
    Hypothesis: Using the object geometry and simulated physics in a particle filterfor an RFID reader can improve localization accuracy
    Method: Particle filter combined with physics-based simulator
    Neeti Shared Wagle
  • Reactive Coverage with Connectivity Constraints
    Problem: cover an environment while maintain connectivity
    Hypothesis: Constraints can be encoded in a global cost function
    Method: Stability analysis of gradient-based controller
  • Probabilistic Path Generation for Data Ferrying in Unknown Sensor Deployments
    Problem: collecting data from sensor network using mobile robot
    Hypothesis: optimal planning always better or same than randomized even if node location is unknown
    Method: analysis and hardware validation
    Anthony Carfang
  • Policy-space Learning of Tunable Locomotion Primitives
    Problem: learn to locomote unknown actuator configurations
    Hypothesis: The Natural Policy Gradient method can allow to find optimal policies in high-dimensional, continuous state space in real time
    Method: implementation in realistic simulation
    Ben Pearre
  • Resource sharing in Multi-Robot Systems
    Problem: improve individual performance by relying on team sensors
    Hypothesis: Can Resource Sharing Make Up for Perception Deficiencies in a Multi-Robot Team?
    Method: Demonstration in real hardware
    Peter Klein
  • Informed Flocking in Honey Bees
    Question: how do honeybees communicate the location of a new nesting site
    Hypothesis: Can the Robustness to Disturbances Shed Light into the Preferred Method of Informed Flocking in Honey-Bees?
    Approach: mathematical model and numerical simulation
    Apratim Shaw
  • Mothership/Daughtership Coverage Control Problem
    Question: how to best distribute capabilities in a system?
    Hypothesis: A hierarchical mothership (MS)/daughtership (DS) system can be applied to coverage control problems and is more efficient and scalable than a team of all MS or all DS.
    Method: mathematical model and numerical simulation
    Jason Durrie
  • An agent based approach to music generation
    Problem: generate nice music automatically
    Hypothesis: A threshold agent based model where each agent represents a note on the piano is capable of creating “good” sounding music.
    Approach: mathematical model and numerical simulation
    Stephen Heck
  • MROS: Multi-Robot Operating System
    Problem: message passing in ROS limited to a single agent
    Hypothesis: broadcast message proxies can turn local message bus into message graph
    Implementation: Message proxy using BioNet
  • Smart Sand
    Problem: Mapping hard to access environments
    Hypothesis: We can reconstruct the topology and sensing landscape of a cavity using large numbers of smart spheres that can establish their local position
    Method: implementation in ODE, analysis
    Monish Prabhakar
  • Towards Truly Soft Robots
    Problem: Creating shape deformation and actuation from soft components
    Hypothesis: Given a soft smart sheet composed of cells that can be individuallyactuated and that can as a result actively change its shape, it is possible to createarbitrary 3D polygons by combining and contorting the 1D sheets in novel ways
    Method: Implementation of spring-mass model of actuator meshes in ODE
  • Optimal plant placement
    Problem: place plants such that light and water are optimally used
    Hypothesis: Genetic algorithms will outperform gradient-based optimization in strongly-coupled, non-linear dynamic systems
    Method: Mathematical model, numerical simulation
    Rhonda Hoenigman
  • Implementation
    Common resources/goals
    Mobile base
    Create clusters and collaborate
  • Project report
    Motivation for your research
    Materials and Methods
  • Scientific thesis in general
    Principally you need a hypothesis and write a dissertation to defend it
    The reality is often different
    Investigate interesting problem and variations
    Funding driven (not necessarily scientific)
    Change in direction/advising
    Solution: what is the most interesting question my material can answer? Drop all the rest.
  • This week
    Wednesday: Probabilistic Modeling
    Friday: Start course projects