Pallet Pose Estimation with LIDAR and Vision for Autonomous Forklifts (original) (raw)
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Pallet Recognition for Forklift: A Literature Review
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023
Forklift trucks are essential tools for manual pallet handling. Storage heights at high rack storage areas often reach up to 12 meters in which bulky Cargo can hide the view of forklift operator. Pallet recognition is a fundamental issue for Industries & warehouses, Particularly, a pallet recognition approach is presented to recognize pallets in the warehouses, based on calculating the degree of similarity at each location of the palette. Once a pallet has been recognized, it is matched that data with stored data. Transporting and handling pallets in a storage area is the essential function of a forklift truck. The view of the forklift truck driver is limited during his work by the lift pole, the fork, and the roof of the forklift truck. If a pallet is loaded the view is additionally hindered by its load. When the storage rack is not at a ground level or near to it the pallet handling becomes more difficult because of the distance between the forklift truck driver and the storage rack. To support the forklift truck driver during his work, there is need to advance the forklifts with different technologies and systems which provide diversity in Working and safety, security for forklift operator and other workers. This paper shows various results from research on different pallet recognition and forklift operation systems.
Using 3D camera technology on forklift trucks for detecting pallets
2012
Forklift trucks are indispensable tools for manual pallet handling. Storage heights at high rack storage areas often reach up to 12 meters which in combination with bulky cargo hinder the view of the forklift truck driver. As part of the joint research project ISI-WALK [1], a 3D-camera-based assistance system is developed at the Institute of Transport and Automation Technology (ITA) to aid the forklift driver especially under limited view conditions. The employed cameras, developed by PMDTechnologies, are integrated into the tips of the forks, thus allowing the detection of pallets and storage racks even if a pallet is already loaded.
Pallet Recognition for Forklift
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023
Pallet recognition is an important task in warehouse operations that involves identifying and classifying pallets based on their size, shape, and colour. The efficient and accurate recognition of pallets is crucial for ensuring the smooth and safe movement of goods within a warehouse. In recent years, advancements in computer vision technology have paved the way for the development of automated pallet recognition systems that can be integrated with forklifts.
Experimental Evaluation of Depth Cameras for Pallet Detection and Pose Estimation
2021
AGVs are widely used for automatic handling of goods in industrial environments, often using some kind of standardized pallets as a platform. Conventionally used AGVs require well-defined, structured and obstacle-free working environments. To work in a dynamic environment, where the exact places of the handled pallets are not necessarily known, the pallet handler needs to detect the target pallets from its environment and localise them accurately enough for manipulation. This can be done using model-based pattern recognition approaches or data-intensive deep learning approaches. Regardless of the chosen approach, the algorithm needs data to work with, which could be conventional image data or depth data. Depth data produced by laser scanners or depth cameras can be used for accurate pose estimation. This thesis aims to evaluate depth cameras while proposing criteria that future depth cameras can be evaluated against. The evaluation should focus on the needs of a target application, ...
On visionsystems for pallet identification and positioning for autonomous warehouse vehicles
2017
Linköpings universitet g n i p ö k r r o N 4 7 Upphovsrätt Detta dokument hålls tillgängligt på Internet-eller dess framtida ersättareunder en längre tid från publiceringsdatum under förutsättning att inga extraordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Överföring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och tillgängligheten finns det lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/ Copyright The publishers will keep this document online on the Internet-or its possible replacement-for a considerable time from the date of publication barring exceptional circumstances. The online availability of the document implies a permanent permission for anyone to read, to download, to print out single copies for your own use and to use it unchanged for any non-commercial research and educational purpose.
UAV Visual and Laser Sensors Fusion for Detection and Positioning in Industrial Applications
Sensors (Basel, Switzerland), 2018
This work presents a solution to localize Unmanned Autonomous Vehicles with respect to pipes and other cylindrical elements found in inspection and maintenance tasks both in industrial and civilian infrastructures. The proposed system exploits the different features of vision and laser based sensors, combining them to obtain accurate positioning of the robot with respect to the cylindrical structures. A probabilistic (RANSAC-based) procedure is used to segment possible cylinders found in the laser scans, and this is used as a seed to accurately determine the robot position through a computer vision system. The priors obtained from the laser scan registration help to solve the problem of determining the apparent contour of the cylinders. In turn this apparent contour is used in a degenerate quadratic conic estimation, enabling to visually estimate the pose of the cylinder.
Laser ranging and video imaging for bin picking
Assembly Automation, 2003
This paper describes an imaging system that was developed to aid industrial bin-picking tasks. The purpose of this system was to provide accurate 3D models of parts and objects in the bin, so that precise grasping operations could be performed. The t echnology described here is based on two types of sensors: range mapping scanners and video cameras. The geometry of bin contents was reconstructed from range maps and modeled using superquadric representations, providing location and parts surface informa tion that can be employed to guide the robotic arm. Video input served for tracking of the manipulator arm, allowing for path validation through pose estimation techniques. Texture was also provided by the video streams and applied to the recovered models. The system is expected to improve the accuracy and efficiency of bin sorting and represents a step toward full automation.
Proceedings of SPIE, 2006
The National Institute of Standards and Technology (NIST) has been studying pallet visualization for the automated guided vehicle (AGV) industry. Through a cooperative research and development agreement with Transbotics, an AGV manufacturer, NIST has developed advanced sensor processing and world modeling algorithms to verify pallet location and orientation with respect to the AGV. Sensor processing utilizes two onboard AGV, single scan-line, laser-range units. The "Safety" sensor is a safety unit located at the base of a forktruck AGV and the "Panner" sensor is a panning laser-ranger rotated 90 degrees, mounted on a rotating motor, and mounted at the top, front of the AGV. The Safety sensor, typically used to detect obstacles such as humans, was also used to detect pallets and their surrounding area such as the walls of a truck to be loaded with pallets. The Panner, was used to acquire many scan-lines of range data which was processed into a 3D point cloud and segment out the pallet by a priori, approximate pallet load or remaining truck volumes. A world model was then constructed and output to the vehicle for pallet/truck volume verification. This paper will explain this joint government/industry project and results of using LADAR imaging methods.
Pose estimation of texture-less cylindrical objects in bin picking using sensor fusion
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016
We propose an approach for emptying of bin using a combination of Image and Range sensor. Offering a complete solution: calibration, segmentation and pose estimation, along with approachability analysis for the estimated pose. The work is novel in the sense that the objects to be picked are featureless and uniformly black in colour, hence existing approaches are not directly applicable. A key point involves optimal utilization of range data acquired from the laser scanner for 3-D segmentation using localized geometric information. This information guides segmentation of the image for better object pose estimation, used for pick-and-drop. We analytically assure the approachability of the object to avoid collision of the manipulator with the bin. Disturbance of objects caused during pick up has been modelled, which allows pickup of multiple pellets based on information from a single range scan. This eliminates the necessity of repeated scanning and data conditioning. The proposed method offers high object detection rate and pose estimation accuracy. The innovative techniques aimed at reducing the average pickup time makes it suitable for robust industrial operation.