Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Modular Robots & Multi-Agent Systems
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Kilobot: A Low Cost Scalable Robot System for Collective BehaviorsIn current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, a low-cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only $14 worth of parts and takes 5 minutes to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems.
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Programming and Controlling Self-Folding SheetsThis paper describes a robot in the form of a self-folding sheet that is capable of origami-style autonomous folding. We describe the hardware device we designed and fabricated. The device is a sheet with a box-pleated pattern and an integrated electronic substrate and actuators. The sheet is programmed and controlled to achieve different shapes using an idea called sticker programming. We describe the sticker controller and its instantiation. We also describe the algorithms for programming and controlling a given sheet to self-fold into a desired shape. Finally we present experiments with a 4x4 hardware device and an 8x8 hardware device.
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Task Allocation with Executable Coalitions in Multirobot TasksIn our prior work, we proposed the IQ-ASyMTRe architecture with a measure of information quality to reason about forming coalitions in multirobot tasks. The formed coalitions are guaranteed to be executable, given the current configurations of the robots and environment. A cost and a quality measure are associated with each coalition to further determine its utility for the task. In this paper, we show that IQ-ASyMTRe-like architectures can be utilized to significantly reduce the overall complexity of task allocation by considering only executable coalitions. For implementation, we apply a layering technique such that most existing methods for task allocation can be easily incorporated. Furthermore, we introduce a general process to address situations in which no executable coalitions are available for certain tasks, and integrate it with IQ-ASyMTRe to achieve more autonomy. Such an approach is able to autonomously decompose unsatisfied preconditions of the required task behaviors into satisfiable components, in order to generate partial order plans for them accordingly. We show how this process can be implemented using a market-based approach. Simulation results are provided to demonstrate these techniques.
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Mathematical Programming for Multi-Vehicle Motion Planning ProblemsReal world Multi-Vehicle Motion Planning (MVMP) problems require the optimization of suitable performance measures under an array of complex and challenging constraints involving kinematics, dynamics, communication connectivity, target tracking, and collision avoidance. The general MVMP problem can thus be formulated as a mathematical program (MP). In this paper we present a mathematical programming (MP) framework that captures the salient features of the general MVMP problem. To demonstrate the use of this framework for the formulation and solution of MVMP problems, we examine in detail four representative works and summarize several other related works. As MP solution algorithms and associated numerical solvers continue to develop, we anticipate that MP solution techniques will be applied to an increasing number of MVMP problems and that the framework and formulations presented in this paper may serve as a guide for future MVMP research.
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Decentralized Multi-Robot Cooperation with Auctioned POMDPsPlanning under uncertainty faces a scalability problem when considering multi-robot teams, as the information space scales exponentially with the number of robots. To address this issue, this paper proposes to decentralize multi-agent Partially Observable Markov Decision Process (POMDPs) while maintaining cooperation between robots by using POMDP policy auctions. Also, communication models in the multi-agent POMDP literature severely mismatch with real inter-robot communication. We address this issue by applying a decentralized data fusion method in order to efficiently maintain a joint belief state among the robots. The paper focuses on a cooperative tracking application, in which several robots have to jointly track a moving target of interest. The proposed ideas are illustrated in real multi-robot experiments, showcasing the flexible and robust cooperation that our techniques can provide.
- All Sessions
- Teleoperation
- Applied Machine Learning
- Biomimetics
- Micro - Nanoscale Automation
- Multi-Legged Robots
- Localization II
- Results of ICRA 2011 Robot Challenge
- Continuum Robots
- Robust and Adaptive Control of Robotic Systems
- Hand Modeling and Control
- Multi-Robot Systems 1
- Medical Robotics I
- Micro/Nanoscale Automation II
- Visual Learning
- AI Reasoning Methods
- Redundant robots
- High Level Robot Behaviors
- Biologically Inspired Robotics
- Novel Robot Designs
- Compliance Devices and Control
- Video Session
- Range Imaging
- Collision
- Localization and Mapping
- Climbing Robots
- Embodied Inteligence - iCUB
- Underactuated Grasping
- Data Based Learning
- Medical Robotics II
- Vision-Based Attention and Interaction
- Control and Planning for UAVs
- Industrial Robotics
- Human Detection and Tracking
- Trajectory Planning and Generation
- Stochastic Motion Planning
- Novel Actuation Technologies
- Micro/Nanoscale Automation III
- Human Like Biped Locamotion
- Embodied Soft Robots
- Mapping
- SLAM I
- Image-Guided Interventions
- Simulation and Search in Grasping
- Control of UAVs
- Grasp Planning
- Marine Robotics II
- Force & Tactile Sensors
- Motion Path Planning I
- Mobile Manipulation: Planning & Control
- Octopus-Inspired Robotics
- Soft Tissue Interaction
- Pose Estimation
- Humanoid Motion Planning and Control
- Surveillance
- Environment Mapping
- Intelligent Manipulation Grasping
- Formal Methods
- Sensor Networks
- Cable-Driven Mechanisms
- Parallel Robots
- SLAM II
- Physical Human-Robot Interaction
- Robotic Software, Programming Environments, and Frameworks
- Minimally invasive interventions I
- Force, Torque and Contacts in Grasping and Assembly
- Hybrid Legged Robots
- Visual Tracking
- Calibration and Identification
- Compliant Nanopositioning
- Micro and Nano Robots I
- Multi-Robot Systems II
- Grasping: Learning and Estimation
- Non-Holonomic Motion Planning
- Motion Planning II
- Estimation and Control for UAVs
- Multi Robots: Task Allocation
- 3D Surface Models, Point Cloud Processing
- Needle Steering
- Networked Robots
- Grasping and Manipulation
- Mechanism Design of Mobile Robots
- Bipedal Robot Control
- Navigation and Visual Sensing
- Localization
- Perception for Autonomous Vehicles
- Rehabilitation Robotics
- Modular Robots & Multi-Agent Systems
- Grasping: Modeling, Analysis and Planning
- Learning and Adaptive Control of Robotic Systems I
- Marine Robotics I
- Autonomy and Vision for UAVs
- RGB-D Localization and Mapping
- Micro and Nano Robots II
- Embodied Intelligence - Complient Actuators
- Biologically Inspired Robotics II
- Underactuated Robots
- Animation & Simulation
- Planning and Navigation of Biped Walking
- Sensing for manipulation
- Sampling-Based Motion Planning
- Minimally Invasive Interventions II
- Stochastic in Robotics and Biological Systems
- Path Planning and Navigation
- Semiconductor Manufacturing
- Haptics
- Learning and Adaptation Control of Robotic Systems II
- Parts Handling and Manipulation
- Space Robotics