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نتیجه جستجو - دستکاری ربات

تعداد مقالات یافته شده: 4
ردیف عنوان نوع
1 Geometric backtracking for combined task and motion planning in robotic systems
بازخوانی هندسی برای کارهای ترکیبی و برنامه ریزی حرکت در سیستم های رباتیک-2017
Article history:Received in revised form 10 February 2015 Accepted 21 March 2015Available online 14 May 2015Keywords:Combined task and motion planning Task planningAction planning Path planning RoboticsGeometric reasoning Hybrid reasoning Robot manipulationPlanners for real robotic systems should not only reason about abstract actions, but also about aspects related to physical execution such as kinematics and geometry. We present an approach to hybrid task and motion planning, in which state-based forward-chaining task planning is tightly coupled with motion planning and other forms of geometric reasoning. Our approach is centered around the problem of geometric backtracking that arises in hybrid task and motion planning: in order to satisfy the geometric preconditions of the current action, a planner may need to reconsider geometric choices, such as grasps and poses, that were made for previous actions. Geometric backtracking is a necessary condition for completeness, but it may lead to a dramatic computational explosion due to the large size of the space of geometric states. We explore two avenues to deal with this issue: the use of heuristics based on different geometric conditions to guide the search, and the use of geometric constraints to prune the search space. We empirically evaluate these different approaches, and demonstrate that they improve the performance of hybrid task and motion planning. We demonstrate our hybrid planning approach in two domains: a real, humanoid robotic platform, the DLR Justin robot, performing object manipulation tasks; and a simulated autonomous forklift operating in a warehouse. 2015 Elsevier B.V. All rights reserved.
Keywords:Combined task and motion planning | Task planning | Action planning | Path planning | Robotics | Geometric reasoning | Hybrid reasoning | Robot manipulation
مقاله انگلیسی
2 Tracking elastic deformable objects with an RGB-D sensor for a pizza chef robot
ردیابی اشیاء قابل تغییر ارتجاعی با یک سنسور RGB-D برای ربات سرآشپز پیتزا-2017
Article history:Received 30 July 2015Received in revised form 20 May 2016 Accepted 25 August 2016Available online 13 September 2016Keywords:PerceptionDeformable object modeling RegistrationRobotic manipulationThis paper presents a method for tracking a 3D textureless object which undergoes elastic deformations, using the point cloud data provided by an RGB-D sensor and in real-time. This solution is expected to be useful for enhanced manipulation of humanoid robotic systems, especially in the case of pizza dough to be ideally manipulated by a pizza chef robot. Our tracking framework relies on a prior visual segmentation of the object in the image. The segmented point cloud is registered first in a rigid manner and then by non-rigidly fitting the mesh, based on the Finite Element Method to model elasticity, and on geometrical point-to-point correspondences to compute external forces exerted on the mesh. The system has been evaluated on synthetic and real data, and by integrating it into manipulation experiments on the RoDyMan1 humanoid robotic platform.© 2016 Elsevier B.V. All rights reserved.
Keywords:Perception | Deformable object modeling | Registration | Robotic manipulation
مقاله انگلیسی
3 Integration of a stereo vision system into an autonomous underwater vehicle for pipe manipulation tasks
یکپارچه سازی یک سیستم بینایی استریو به یک وسیله نقلیه زیرزمینی مستقل برای وظایف دستکاری لوله-2017
Article history:Received 3 June 2016Revised 30 August 2016Accepted 30 August 2016Available online 8 September 2016Keywords:Underwater computer vision Robot manipulationStereo processing Object detectionUnderwater object detection and recognition using computer vision are challenging tasks due to the poor light condition of submerged environments. For intervention missions re- quiring grasping and manipulation of submerged objects, a vision system must provide an Autonomous Underwater Vehicles (AUV) with object detection, localization and tracking capabilities. In this paper, we describe the integration of a vision system in the MARIS intervention AUV and its configuration for detecting cylindrical pipes, a typical artifact of interest in underwater operations. Pipe edges are tracked using an alpha-beta filter to achieve robustness and return a reliable pose estimation even in case of partial pipe vis- ibility. Experiments in an outdoor water pool in different light conditions show that the adopted algorithmic approach allows detection of target pipes and provides a sufficiently accurate estimation of their pose even when they become partially visible, thereby sup- porting the AUV in several successful pipe grasping operations.© 2016 Elsevier Ltd. All rights reserved.
Keywords: Underwater computer vision | Robot manipulation | Stereo processing | Object detection
مقاله انگلیسی
4 Teaching robots to do object assembly using multi-modal 3D vision
آموزش ربات ها برای انجام مونتاژ چهره با استفاده از دید مدل 3D-2017
Article history:Received 25 January 2016Revised 2 October 2016Accepted 16 January 2017Available online 7 February 2017Keywords:3D visual detection Robot manipulation Motion planningThe motivation of this paper is to develop an intelligent robot assembly system using multi-modal vision for next-generation industrial assembly. The system includes two phases where in the first phase human beings demonstrate assembly to robots and in the second phase robots detect objects, plan grasps, and assemble objects following human demonstration using AI searching. A notorious difficulty to implement such a system is the bad precision of 3D visual detection. This paper presents multi-modal approaches to overcome the difficulty: It uses AR markers in the teaching phase to detect human operation, and uses point clouds and geometric constraints in the robot execution phase to avoid unexpected occlu- sion and noises. The paper presents several experiments to examine the precision and correctness of the approaches. It demonstrates the applicability of the approaches by integrating them with graph model- based motion planning, and by executing the results on industrial robots in real-world scenarios.© 2017 Elsevier B.V. All rights reserved.
Keywords: 3D visual detection | Robot manipulation | Motion planning
مقاله انگلیسی
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