Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Industrial Robotics
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Tool Position Estimation of a Flexible Industrial Robot Using Recursive Bayesian MethodsA sensor fusion method for state estimation of a flexible industrial robot is presented. By measuring the acceleration at the end-effector, the accuracy of the arm angular position is improved significantly when these measurements are fused with motor angle observation. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; one using the extended Kalman filter (EKF) and one using the particle filter (PF). The technique is verified on experiments on the ABB IRB4600 robot, where the accelerometer method is showing a significant better dynamic performance, even when model errors are present.
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A Sensor-Based Approach for Error Compensation of Industrial Robotic WorkcellsIndustrial robotic manipulators have excellent repeatability while accuracy is significantly poorer. Numerous error sources in the robotic workcell contributes to the accuracy problem. Modeling and identification of all the errors to achieve the required levels of accuracy may be difficult. To resolve the accuracy issues, a sensor based indirect error compensation approach is proposed in this paper where the errors are compensated online via measurements of the work object. The sensor captures a point cloud of the work object and with the CAD model of the work object, the actual relative pose of the sensor frame and work object frame can be established via a point cloud registration. Once this relationship has been established, the robot will be able to move the tool accurately relative to the work object frame near the point of compensation. A data pre-processing technique is proposed to reduce computation time and prevent a local minima solution during point cloud registration. A simulation study is presented to illustrate the effectiveness of the proposed solution.
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Robot End-Effector Sensing with Position Sensitive Detector and Inertial SensorsFor the motion control of industrial robots, the end-effector performance is of the ultimate interest. However, industrial robots are generally only equipped with motor-side encoders. Accurate estimation of the end-effector position and velocity is thus difficult due to complex joint dynamics. To overcome this problem, this paper presents an optical sensor based on position sensitive detector (PSD), referred as PSD camera, for direct end-effector position sensing. PSD features high precision and fast response while being cost-effective, thus is favorable for real-time feedback applications. In addition, to acquire good velocity estimation, a kinematic Kalman filter (KKF) is applied to fuse the measurement from the PSD camera with that from inertial sensors mounted on the end-effector. The performance of the developed PSD camera and the application of the KKF sensor fusion scheme have been validated through experiments on an industrial robot.
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Experiments towards Automated Sewing with a Multi-Robot SystemIn this paper a concept for automated multi-robot-aided sewing is presented. The objective of the work is to demonstrate automatic sewing of 3D-shaped covers for recliners, by assembling two different hide parts with different shapes, using two robots to align the parts during sewing. The system consists of an industrial sewing machine and two real-time controlled Universal Robots 6-axis industrial manipulators. A force feedback system combined with optical edge sensors is evaluated for the control of the sewing process. The force sensors are used to synchronize the velocity and feed rate between the robots and the sewing machine. A test cell was built to determine the feasibility of the force feedback control and velocity synchronization. Experiments are presented which investigate the ability of the robot to feed a hide part into the sewing machine using a force sensor and different strategies for velocity synchronization.
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Automated Throwing and Capturing of Cylinder-Shaped ObjectsA new approach for transportation of objects within production systems by automated throwing and capturing is investigated. This paper presents an implementation, consisting of a throwing robot and a capturing robot. The throwing robot uses a linear and the capturing robot a rotary axis. The throwing robot is capable of throwing cylinder-shaped objects onto a target point with high precision. The capturing robot there smoothly grips the cylinders during flight by means of a rotational movement. In order to synchronize the capturing robot and the cylinder’s pose and velocity, its trajectory has to be modeled as well as the motion sequences of both robots. The throwing and capturing tasks are performed by the robots automatically without the use of any external sensor system.
- 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