Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Biomimetics
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Experimental Validation of locomotion efficiency of Worm-like Robots and Contact ComplianceBiological vessels are characterized by their substantial compliance and low friction which present a major challenge for crawling robots for minimally invasive medical procedures. Quite a number of studies considered the design and construction of crawling robots, however, very few focused on the interaction between the robots and the flexible environment. In a previous study, we derived the analytical efficiency of worm locomotion as a function of the number of cells, friction coefficients, normal forces and local (contact) tangential compliance. In this paper, we generalize our previous analysis to include dynamic and static coefficients of friction, determine the conditions of locomotion as function of the external resisting forces and experimentally validate our previous and newly obtained theoretical results. Our experimental setup consists of worm robot prototypes, flexible interfaces with known compliance and a Vicon motion capture system to measure the robot positioning. Separate experiments were conducted to measure the tangential compliance of the contact interface which is required for computing the analytical efficiency. The validation experiments are shown to be in clear match with the theoretical predictions. Specifically, the convergence of the tangential deflections to an arithmetic series and the partial and overall loss of locomotion verify the theoretical predictions.
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Dynamic Turning of 13 Cm Robot Comparing Tail and Differential DriveRapid and consistent turning of running legged robots on surfaces with moderate friction is challenging due to leg slip and uncertain dynamics. A tail is proposed as a method to effect turns at higher yaw frequencies than can be obtained by differential velocity drive of alternate sides. Here we introduce a 100 mm scale dynamic robot - OctoRoACH - with differential-drive steering and a low-mass tail to investigate issues of yaw rate control. The robot without tail is under-actuated with only 2 drive motors and mass of 35 grams including all battery and control electronics. For some surface conditions, OctoRoACH can maintain heading or turning rate using only leg velocity control, and a basic rate-gyro-based heading control system can respond to disturbances, with a closed-loop bandwidth of approximately 1 Hz. Using a modified off-the-shelf servo for the tail drive, the robot responds to turning commands at 4 Hz.
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A Compliant Bioinspired Swimming Robot with Neuro-Inspired Control and Autonomous BehaviorIn this paper the development of a bio-robotic platform is described. The robot design exploits biomechanical and neuroscientific knowledge on the lamprey, an eel-like swimmer well studied and characterized thanks to the reduced complexity of its anatomy. The robot is untethered, has a compliant body, muscle-like high efficiency actuators, proprioceptive sensors to detect stretch and stereoscopic vision. Experiments on the platform are reported, including robust and autonomous goal-directed swimming. Extensive experiments have been possible thanks to very high energy efficiency (around five hour continuous operating) the platform is ready to be used as investigation tool for high level motor tasks.
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Kinematic Design of an Asymmetric In-phase Flapping Mechanism for MAVsThe thorax of an insect has direct flight muscles that can independently control the flapping amplitude, relative phase, and mean position of its left and right wings. This feature allows insects to modulate lateral dynamics during hovering flight, resulting in high flight maneuverability. This paper introduces the development and characterization of a novel flapping mechanism for MAVs, denoted as AIFM (Asymmetric In-phase Flapping Mechanism), that is capable of achieving controlled, asymmetric in-phase wing flapping as inspired by similar features in insects. The system consists of two 4-bar mechanisms that create basic flapping motions and two RRPR mechanisms that control the asymmetric flapping motion. The kinematics of the mechanism was investigated and optimized in such a way that enables the mechanism to produce reliable, in-phase wing motion during asymmetric flapping flight. The kinematics of the wings was evaluated both computationally and experimentally. It was shown that asymmetric wing flapping can be successfully achieved without affecting the in-phase flapping motion.
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Maintaining Odor Tracking Behavior Using an Established Tracking Direction in a Dynamic Wind EnvironmentThe ability to autonomously track a fluid-borne odor has numerous engineering applications and natural occurrences. Engineering systems can use odor-guided navigation in tasks ranging from search and rescue to locating dangerous chemicals. Animals use odors to locate food and mates. For animals in strong unsteady turbulent flow environments where the wind is intermittent and occasionally vanishes, there is an ecological benefit to maintaining wind-driven tracking behavior. This has been shown in experiments performed using moths and cockroaches, where animals that began tracking odor in wind maintained their wind driven tracking behavior and eventually located the source after the wind was shut off during their tracking behavior. Here, we use RoboMoth, a previously developed 3D odor-tracking robot, to replicate these experiments. Our results can aid biologists in understanding how animals track odors in dynamic environments. In engineering, this study provides a first step in a hardware system towards linking odor tracking in strong wind environments to tracking in zero/low flow environments by studying the transition between the two regimes. This can help further engineers’ efforts to design odor-tracking systems capable of negotiating diverse and dynamic environments. Our study of the transition from using the wind as a primary directional cue to relying on odor and an established tracking direction appears to be novel in an engineering context and unique to our work.
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Brain-inspired Bayesian Perception for Biomimetic Robot TouchStudies of decision making in animals suggest a neural mechanism of evidence accumulation for competing percepts according to Bayesian sequential analysis. This model of perception is embodied here in a biomimetic tactile sensing robot based on the rodent whisker system. We implement simultaneous perception of object shape and location using two psychological test paradigms: first, a free-response paradigm in which the agent decides when to respond, implemented with Bayesian sequential analysis; and second an interrogative paradigm in which the agent responds after a fixed interval, implemented with maximum likelihood estimation. A benefit of free-response Bayesian perception is that it allows tuning of reaction speed against accuracy. In addition, we find that large gains in decision performance are achieved with unforced responses that allow null decisions on ambiguous data. Therefore free-response Bayesian perception offers benefits for artificial systems that make them more animal-like in behavior.
- All Sessions
- 3D Surface Models, Point Cloud Processing
- Needle Steering
- Networked Robots
- Grasping and Manipulation
- Motion Planning II
- Estimation and Control for UAVs
- Multi Robots: Task Allocation
- Localization
- Perception for Autonomous Vehicles
- Rehabilitation Robotics
- Modular Robots & Multi-Agent Systems
- Mechanism Design of Mobile Robots
- Bipedal Robot Control
- Navigation and Visual Sensing
- Autonomy and Vision for UAVs
- RGB-D Localization and Mapping
- Micro and Nano Robots II
- Embodied Intelligence - Complient Actuators
- Grasping: Modeling, Analysis and Planning
- Learning and Adaptive Control of Robotic Systems I
- Marine Robotics I
- Animation & Simulation
- Planning and Navigation of Biped Walking
- Sensing for manipulation
- Sampling-Based Motion Planning
- Minimally Invasive Interventions II
- Biologically Inspired Robotics II
- Underactuated Robots
- Semiconductor Manufacturing
- Haptics
- Learning and Adaptation Control of Robotic Systems II
- Parts Handling and Manipulation
- Space Robotics
- Stochastic in Robotics and Biological Systems
- Path Planning and Navigation
- Biomimetics
- Micro - Nanoscale Automation
- Multi-Legged Robots
- Localization II
- Results of ICRA 2011 Robot Challenge
- Teleoperation
- Applied Machine Learning
- Hand Modeling and Control
- Multi-Robot Systems 1
- Medical Robotics I
- Micro/Nanoscale Automation II
- Visual Learning
- Continuum Robots
- Robust and Adaptive Control of Robotic Systems
- High Level Robot Behaviors
- Biologically Inspired Robotics
- Novel Robot Designs
- Compliance Devices and Control
- Video Session
- AI Reasoning Methods
- Redundant robots
- Localization and Mapping
- Climbing Robots
- Embodied Inteligence - iCUB
- Underactuated Grasping
- Data Based Learning
- Range Imaging
- Collision
- Industrial Robotics
- Human Detection and Tracking
- Trajectory Planning and Generation
- Stochastic Motion Planning
- Medical Robotics II
- Vision-Based Attention and Interaction
- Control and Planning for UAVs
- Embodied Soft Robots
- Mapping
- SLAM I
- Image-Guided Interventions
- Novel Actuation Technologies
- Micro/Nanoscale Automation III
- Human Like Biped Locamotion
- Marine Robotics II
- Force & Tactile Sensors
- Motion Path Planning I
- Mobile Manipulation: Planning & Control
- Simulation and Search in Grasping
- Control of UAVs
- Grasp Planning
- Humanoid Motion Planning and Control
- Surveillance
- Environment Mapping
- Octopus-Inspired Robotics
- Soft Tissue Interaction
- Pose Estimation
- Cable-Driven Mechanisms
- Parallel Robots
- SLAM II
- Intelligent Manipulation Grasping
- Formal Methods
- Sensor Networks
- Force, Torque and Contacts in Grasping and Assembly
- Hybrid Legged Robots
- Visual Tracking
- Physical Human-Robot Interaction
- Robotic Software, Programming Environments, and Frameworks
- Minimally invasive interventions I
- Multi-Robot Systems II
- Grasping: Learning and Estimation
- Non-Holonomic Motion Planning
- Calibration and Identification
- Compliant Nanopositioning
- Micro and Nano Robots I