The use of robots has significantly increased to fight highly contagious diseases like SARS-COV-2, Ebola, MERS, and others. One of the important applications of robots to fight such infectious ...diseases is disinfection. Manual disinfection can be a time-consuming, risky, labor-intensive, and mundane, and humans may fail to disinfect critical areas due to the resulting fatigue. Autonomous or semi-autonomous mobile manipulators mounted with a spray nozzle at the end-effector can be very effective in spraying disinfectant liquid for deep disinfection of objects and surfaces. In this paper, we present an area-coverage planning algorithm to compute a path that the nozzle follows to disinfect surfaces represented by their point clouds. We project the point cloud on a plane and produce a polygon on which we generate multiple spray paths using our branch and bound-based tree search area-coverage algorithm such that the spray paths cover the entire area of the polygon. An appropriate spray path is chosen using a robot capability map-based selection criterion. We generate mobile manipulator trajectories using successive refinement-based parametric optimization so that the paths for the nozzle are followed accurately. Thereafter, we need to make sure that the joint velocities of the mobile manipulator are regulated appropriately such that each point on the surface receives enough disinfectant spray. To this end, we compute the time intervals between the robot path waypoints such that enough disinfectant liquid is sprayed on all points of the point cloud that results in thorough disinfection of the surface, and the particular robot path is executed in the minimum possible time. We have implemented the area-coverage planning and mobile manipulator motion planning on five test scenarios in simulation using our ADAMMS-SD (Agile Dexterous Autonomous Mobile Manipulation System for Surface Disinfection) robot. We benchmark our spray path generation algorithm with three competing methods by showing that the generated paths are significantly more efficient in terms of area coverage and reducing disinfectant wastage. We also show the time interval computation between successive waypoints results in thorough disinfection of surfaces.
•Covid-19 and similar viral diseases can spread via surfaces, hence disinfection is important, especially with robots as it reduces human risk and effort.•Mobile manipulators mounted with a spray nozzle can be used autonomously or semi-autonomously to disinfect surfaces.•A branch and bound-based algorithm is presented to determine spray paths on a point cloud of the surfae being disinfected.•A spline-based representation of the robot degrees of freedom and successive refinement-based optimization are used for generating robot motion.•A linear programming-based formulation is used to find the time taken between successive waypoints to guarantee thorough disinfection of surfaces.
Robots are versatile machines that can perform complex manipulation operations. Recent advances in industrial robotics make robots useful in a wide variety of manufacturing processes. Several recent ...efforts have demonstrated how robots can be used in additive manufacturing (AM) processes. This paper surveys the work focused on expanding the functional capabilities of AM processes using robots. We identify the following main capabilities realized by performing AM using robots: (1) multi-directional fabrication, (2) conformal deposition, (3) assembling prefabricated components in AM, (4) supportless AM, and (5) large-scale AM. We classify the recent literature in this area in terms of mechanisms, kinematic degrees of freedom (DOF) of the system, types of AM process, and materials. Finally, we discuss the limitations of the current work and the opportunities for future research in this area.
Automated planning for robotic layup of composite prepreg Malhan, Rishi K.; Shembekar, Aniruddha V.; Kabir, Ariyan M. ...
Robotics and computer-integrated manufacturing,
February 2021, 2021-02-00, 20210201, Letnik:
67
Journal Article
Recenzirano
Odprti dostop
•Automated grasp planning enables a multi-robot cell to determine where to grasp a ply during layup.•Automated robot placement determines the location of the robots to execute complex constrained ...paths in the workspace.•A physics-aware grasp planner and a successive application of constraints-based robot placement planner can handle complex industrial use cases.•The robotic cell is capable of executing layup using the automatically generated plans.
Hand layup is a commonly used process for making composite structures from several plies of carbon-fiber prepreg. The process involves multiple human operators manipulating and conforming layers of prepreg to a mold. The manual layup process is ergonomically challenging, tedious, and limits throughput. Moreover, different operators may perform the process differently, and hence introduce inconsistency. We have developed a multi-robot cell to automate the layup process. A human expert provides a sequence to conform to the ply and types of end-effectors to be used as input to the system. The system automatically generates trajectories for the robots that can achieve the specified layup. Using the cell requires the automated generation of different types of plans. This paper addresses two main planning problems: (a) generating plans to grasp and manipulate the ply and (b) generating feasible robot trajectories. We use a hybrid-physics based simulator coupled with a state space search to find grasp plans. The system employs a strategy that applies constraints successively in a non-linear optimization formulation to identify suitable placements of the robots around the mold so that feasible trajectories can be generated. Our system can generate plans in a computationally efficient manner, and it can handle a wide variety of complex parts. We demonstrate the automated layup by conducting physical experiments on an industry-inspired mold using the generated plans.
We present an approach to generate path-constrained synchronous motion for the coupled ensemble of robots. In this article, we refer to serial-link manipulators and mobile bases as robots. We assume ...that the relative motion constraints among the objects in the environment are given. We represent the motion constraints as path constraints and pose the problem of path-constrained synchronous trajectory generation as a non-linear optimization problem. Our approach generates configuration space trajectories for the robots to manipulate the objects such that the given motion constraints among the objects are satisfied. We present a method that formulates the problem as a discrete parameter optimization problem and solves it using successive constraint refinement techniques. The method adaptively selects the parametric representation of the configuration variables for a given scenario. It also generates an approximate solution as the starting point for the successive constraint refinement stages to reduce the computation time. We discuss in detail why successive constraint refinement strategies are useful for solving this class of problems. We demonstrate the effectiveness of the proposed method on challenging test cases in simulation and physical environments with high-degree-of-freedom robotic systems.
Metal additive manufacturing has revolutionized the manufacturing industry due to its capability of building complex parts without any part-specific tooling. Wire arc metal additive manufacturing is ...a process that uses the arc welding technique to build parts layer by layer. Robotic manipulators equipped with arc welding hardware can perform wire arc additive manufacturing and build complex geometries. In addition, the manipulator’s flexibility expands the capabilities of the additive manufacturing process. However, the geometries of the parts are limited by the flat substrate used for this process. This research aims to overcome this limitation by exploring a conformal substrate for wire arc additive manufacturing. Along with exploring the conformal substrate, this research will close the gap of the technical advancements and experimental validation required to build conformal metal parts. A conformal substrate makes the process planning complex. We address this complexity by making five novel contributions: (1) exploratory experiments with copper and iron as conformal substrate materials to determine if they are appropriate for the build material; (2) development of a corner accumulation detection algorithm for bead defect detection; (3) development of a process-specific tool-path planning algorithm to avoid molten metal from flowing under gravity; (4) development of a substrate placement planning algorithm to fit the trajectory in the manipulator’s workspace; (5) building and characterization of the built parts’ mechanical properties. Five truss-like parts are built using our process planning approach. Three of the truss-like parts are planar, and two truss-like parts are conformal. The parts are characterized to understand the effects of conformal substrate on the microstructure, microhardness, and T-peel strength.
Sensors are widely used to construct a 3D model of parts by collecting data. The accuracy of the collected data depends on sensor placement with respect to the part and sensor operational range. The ...operational range and limitations of the sensor need to be applied as constraints while planning for robot motions that move the sensor around the part to collect data. Overly conservative constraints on sensor placement will lead to high execution times. We present an approach where we develop a robot motion planning algorithm that takes into account the camera performance constraints and produces output with low error. An RGB-D camera is used to obtain the pointcloud of the part. An offline planning method improves point density in the regions having zero or low density. Our method guarantees a high point density across the surface of the part. Results are presented on six geometries with different complexity and surface properties. We also present results on how camera parameters influence the output of our method. Our results show that algorithmic advances reported in this paper enable us to use low-cost depth cameras for producing high accuracy uniform density scans of physical objects.
•Robots enable complex sensor motions by providing high DOF to avoid occlusions.•Sensors have large workspace but only a small region can produce high accuracy data.•Planning constraints based on sensor characteristics need to be enforced.•Online planning is needed for adding points to low-density areas on the pointcloud.•Robotic cell for 3d reconstruction is realized in this work.•Generated paths collect high accuracy pointclouds using selective camera workspace.
Conventional material extrusion additive manufacturing is capable of building complex structures. Overhanging features require the use of support structures. Printing the support structure requires ...additional time and material. Conventional processes need time to remove support material and may lead to degraded surface finish. The use of support structures can be avoided by dynamically reorienting the build-platform. This paper presents a novel approach to build accurate thin shell parts using supportless extrusion-based additive manufacturing. We describe the layer slicing algorithm, the tool-path planning algorithm, and the neural network-based compensated trajectory generation scheme to use a 3 degree of freedom build-platform and a 3 degree of freedom extrusion tool to build accurate thin shell parts using two manipulators. Such thin shell parts cannot be built without supports by previous supportless AM processes. We illustrate the usefulness of our algorithms by building several thin shell parts.
Serial-link manipulators are required to execute trajectories that enable a robot end-effector or a tool to track a Cartesian path. Practical applications may not require constraining all six degrees ...of freedom (position and orientation) of the tool resulting in semi-constrained paths. Semi-constrained paths allow improved success rates and better quality trajectories as the robot has more freedom to meet the kinematic and dynamic constraints. Additionally, robotic applications will need to use multiple tool center points (TCPs) on the tool to generate feasible paths for the robot. We present an iterative graph construction method to find trajectories for semi-constrained Cartesian paths that also use multiple TCPs. Our graph-based method finds multiple inverse kinematic solutions for possible Cartesian poses that the robot can take and connects them to build a graph. The algorithm uses cues from the Cartesian space to prioritize poses that produce a better quality solution. A biasing scheme is also developed to selectively sample the starting Cartesian poses from available choices. Our method finds near-optimal solutions with significantly fewer nodes and edges in the graph. The algorithm's performance results on complex industrial test cases are provided. Note to Practitioners-Industrial applications permit the relaxation of one or more degrees of freedom of the tool while following the Cartesian paths. The relaxation of constraints is introduced by defining tolerances between the tool and the workpiece. Multiple TCPs have to be employed for many tasks to use different surfaces of the tool. In this paper, we present a planning algorithm for semi-constrained Cartesian paths that can incorporate the use of multiple TCPs. The user can define discrete TCPs over the tool contact points or surfaces. The tolerances can be easily defined as angular limits on tool orientation along the Cartesian path. Our planning algorithm can work with others via point constraints in Cartesian space or joint space of the robot. Practitioners from the industry can use the method presented in this paper to develop automated robotic cells that do cutting, sanding, polishing, welding, painting, composite layup, additive manufacturing, and several other common applications.
Robotic manipulators are increasingly being used to perform additive manufacturing. The accuracy of a built part is dependent on the trajectory execution error of the manipulator. For articulated ...manipulators, the trajectory execution error and achievable build accuracy vary considerably over the workspace. Therefore, the build accuracy depends on where the part is placed in the manipulator workspace. If the part is small compared to the manipulator workspace, its placement can be optimized to improve the accuracy. This paper provides experimental evidence that the placement of the parts changes its build accuracy. We model the trajectory execution error of the manipulator for additive manufacturing. We validate these errors by comparing the predicted errors with the experimental errors. Finally, we present an algorithm to optimize the part placement for improving built part accuracy during robot-based additive manufacturing.
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