Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Embodied Soft Robots
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Design and Development of a Soft Robotic Octopus Arm Exploiting Embodied IntelligenceThe octopus is a marine animal whose body has no rigid structures. It has eight arms mainly composed of muscles organized in a peculiar structure, named muscular hydrostat, that can change stiffness and that is used as a sort of a modifiable skeleton. Furthermore, the morphology of the arms and the mechanical characteristics of their tissues are such that the interaction with the environment, namely water, is exploited to simplify the control of movements. From these considerations, the octopus emerges as a paradigmatic example of embodied intelligence and a good model for soft robotics. In this paper the design and the development of an artificial muscular hydrostat are reported, underling the efforts in the design and development of new technologies for soft robotics, like materials, mechanisms, soft actuators. The first prototype of soft robot arm is presented, with experimental results that show its capability to perform the basic movements of the octopus arm (like elongation, shortening, and bending) and demonstrate how embodiment can be effective in the design of robots.
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The Application of Embodiment Theory to the Design and Control of an Octopus-Like Robotic ArmThis paper examines the design and control of a robotic arm inspired by the anatomy and neurophysiology of Octopus vulgaris in light of embodiment theory. Embodiment in an animal is defined as the dynamic coupling between sensory-motor control, anatomy, materials, and the environment that allows for the animal to achieve effective behaviour. Octopuses in particular are highly embodied and dexterous animals: their arms are fully flexible, can bend in any direction, grasp objects and modulate stiffness along their length. In this paper the biomechanics and neurophysiology of octopus have been analysed to extract relevant information for use in the design and control of an embodied soft robotic arm. The embodied design requirements are firstly defined, and how the biology of the octopus meets these requirements presented. Next, a prototype continuum arm and control architecture based on octopus biology, and meeting the design criteria, are presented. Finally, experimental results are presented to show how the developed prototype arm is able to reproduce motions performed by live octopus for contraction, elongation, bending, and grasping.
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Dynamic Continuum Arm Model for Use with Underwater Robotic Manipulators Inspired by Octopus VulgarisContinuum structures with a very high or infinite number of degrees of freedom (DOF) are very interesting structures in nature. Mimicking this kind of structures artificially is challenging due to the high number of required DOF. This paper presents a kinematic and dynamic model for an underwater robotic manipulator inspired by Octopus vulgaris. Then, a prototype arm inspired by live octopus is presented and the model validated experimentally. Initial comparisons of simulated and experimental results show good agreement.
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Hydrodynamic Analysis of Octopus-Like Robotic ArmsWe consider robotic analogues of the arms of the octopus, a cephalopod exhibiting a wide variety of dexterous movements and complex shapes, moving in an aquatic environment. Although an invertebrate, the octopus can vary the stiffness of its long arms and generate large forces, while also performing rapid motions within its aquatic environment. Previous studies of elongated robotic systems, moving in fluid environments, have mostly oversimplified the effects of flow and the generated hydrodynamic forces, in their dynamical models. The present paper uses computational fluid dynamic (CFD) analysis to perform high-fidelity numerical simulations of robotic prototypes emulating the morphology of octopus arms. The direction of the flow stream and the arm geometry (e.g., the presence of suckers), were among the parameters that were shown to affect significantly the flow field structure and the resulting hydrodynamic forces, which have a non-uniform distribution along the arm. The CFD results are supported by vortex visualization experiments in a water tank. The results of this investigation are being exploited for the design of soft-bodied robotic systems and the development of related motion control strategies.
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Design and Performance of Nubbed Fluidizing Jamming GrippersGrippers have been shown using jamming of granular media grasp a large range of objects by pushing against them (with an activation force) to conform the gripper to the object’s shape before grasping them with the intent to make universal grippers. This paper presents two effective modifications to jamming gripper designs (adding small nubs and fluidizing the granular media) resulting in significantly larger holding forces (typically 60%) and increasing the range of object geometries. The paper presents the design and fabrication of these devices and explores the range of objects and conditions empirically. Experiments also show that the nubs enable the grasping of smaller objects in which the gripper can engage interlocking forces in the granular media.
- All Sessions
- Modular Robots & Multi-Agent Systems
- Mechanism Design of Mobile Robots
- Bipedal Robot Control
- Navigation and Visual Sensing
- Localization
- Perception for Autonomous Vehicles
- Rehabilitation Robotics
- Embodied Intelligence - Complient Actuators
- 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
- Minimally Invasive Interventions II
- Biologically Inspired Robotics II
- Underactuated Robots
- Animation & Simulation
- Planning and Navigation of Biped Walking
- Sensing for manipulation
- Sampling-Based Motion Planning
- Space Robotics
- 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
- Results of ICRA 2011 Robot Challenge
- Teleoperation
- Applied Machine Learning
- Biomimetics
- Micro - Nanoscale Automation
- Multi-Legged Robots
- Localization II
- Micro/Nanoscale Automation II
- Visual Learning
- Continuum Robots
- Robust and Adaptive Control of Robotic Systems
- Hand Modeling and Control
- Multi-Robot Systems 1
- Medical Robotics I
- Compliance Devices and Control
- Video Session
- AI Reasoning Methods
- Redundant robots
- High Level Robot Behaviors
- Biologically Inspired Robotics
- Novel Robot Designs
- Underactuated Grasping
- Data Based Learning
- Range Imaging
- Collision
- Localization and Mapping
- Climbing Robots
- Embodied Inteligence - iCUB
- Stochastic Motion Planning
- Medical Robotics II
- Vision-Based Attention and Interaction
- Control and Planning for UAVs
- Industrial Robotics
- Human Detection and Tracking
- Trajectory Planning and Generation
- Image-Guided Interventions
- Novel Actuation Technologies
- Micro/Nanoscale Automation III
- Human Like Biped Locamotion
- Embodied Soft Robots
- Mapping
- SLAM I
- Mobile Manipulation: Planning & Control
- Simulation and Search in Grasping
- Control of UAVs
- Grasp Planning
- Marine Robotics II
- Force & Tactile Sensors
- Motion Path Planning I
- Environment Mapping
- Octopus-Inspired Robotics
- Soft Tissue Interaction
- Pose Estimation
- Humanoid Motion Planning and Control
- Surveillance
- SLAM II
- Intelligent Manipulation Grasping
- Formal Methods
- Sensor Networks
- Cable-Driven Mechanisms
- Parallel Robots
- Visual Tracking
- 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
- Non-Holonomic Motion Planning
- Calibration and Identification
- Compliant Nanopositioning
- Micro and Nano Robots I
- Multi-Robot Systems II
- Grasping: Learning and Estimation
- Grasping and Manipulation
- Motion Planning II
- Estimation and Control for UAVs
- Multi Robots: Task Allocation
- 3D Surface Models, Point Cloud Processing
- Needle Steering
- Networked Robots