61 research outputs found

    Comparative analysis of firefly algorithm for solving optimization problems

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    Firefly algorithm was developed by Xin-She Yang [1] by taking inspiration from flash light signals which is the source of attraction among fireflies for potential mates. All the fireflies are unisexual and attract each other according to the intensities of their flash lights. Higher the flash light intensity, higher is the power of attraction and vice versa. For solving optimization problem, the brightness of flash is associated with the fitness function to be optimized. The light intensity I (r) of a firefly at distance r is given by equation (1

    On-the-Fly Workspace Visualization for Redundant Manipulators

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    This thesis explores the possibilities of on-line workspace rendering for redundant robotic manipulators via parallelized computation on the graphics card. Several visualization schemes for different workspace types are devised, implemented and evaluated. Possible applications are visual support for the operation of manipulators, fast workspace analyses in time-critical scenarios and interactive workspace exploration for design and comparison of robots and tools

    Safety analysis on human-robot collaboration in heavy assembly task

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    Manufacturing assembly industry has traditionally utilized human labor to perform assembly tasks manually. With the introduction of industrial robots, fully automated solutions have provided an opportunity to perform complex and repetitive tasks and assist in the assembly of heavy components. In recent years, improvement in robot technologies and changes in safety legislation have enabled new human-robot collaboration (HRC) concepts which have drawn attention of manufacturers. HRC uses characteristics of dexterity and flexibility of human and repeatability and precision of robots to increase the flexibility of the system, decrease the cost of labor in production and improve ergonomics in the design of shared workspace. The operator safety is one of the challenges inside the HRC environment. The safety concerns could be altered with different levels of physical interactions between robot and human. This thesis aimed to develop solution for analyzing the safety functions on different human-robot interaction (HRI) levels. The approach was started with the classification of tasks between human and robot. In this thesis, assembly sequences were designed to fulfill the requirements of each interaction levels of HRI. These experiments were providing evaluation tables for analyzing the safety functions in HRI levels. The primary objective of this thesis is to design the HRC system with suitable safety functions. The safety of the workstation was developed using a combination of hardware and software. Laser scanners employed to detect the presence of a human in hazard areas and ABB SafeMove add-on were configured to exploit safety signals to the robot controller for adopting safety functions such as safety-rated monitored stop, and speed and separation monitoring. In this thesis, time work study analysis was demonstrated that the implementation of HRC decreases the fatigue and the injury risks of the operator and enhances the ergonomics for the operators. The study of safety functions through different HRI levels proved that with an increase of physical interactions it was necessary to employ multiple safety functions to prohibit collisions between robot and human

    Fast-dRRT*: Efficient Multi-Robot Motion Planning for Automated Industrial Manufacturing

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    We present Fast-dRRT*, a sampling-based multi-robot planner, for real-time industrial automation scenarios. Fast-dRRT* builds upon the discrete rapidly-exploring random tree (dRRT*) planner, and extends dRRT* by using pre-computed swept volumes for efficient collision detection, deadlock avoidance for partial multi-robot problems, and a simplified rewiring strategy. We evaluate Fast-dRRT* on five challenging multi-robot scenarios using two to four industrial robot arms from various manufacturers. The scenarios comprise situations involving deadlocks, narrow passages, and close proximity tasks. The results are compared against dRRT*, and show Fast-dRRT* to outperform dRRT* by up to 94% in terms of finding solutions within given time limits, while only sacrificing up to 35% on initial solution cost. Furthermore, Fast-dRRT* demonstrates resilience against noise in target configurations, and is able to solve challenging welding, and pick and place tasks with reduced computational time. This makes Fast-dRRT* a promising option for real-time motion planning in industrial automation.Comment: 7 pages, 6 figures, submitted to ICRA 202

    Automatic motion of manipulator using sampling based motion planning algorithms - application in service robotics

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    The thesis presents new approaches for autonomous motion execution of a robotic arm. The calculation of the motion is called motion planning and requires the computation of robot arm's path. The text covers the calculation of the path and several algorithms have been therefore implemented and tested in several real scenarios. The work focuses on sampling based planners, which means that the path is created by connecting explicitly random generated points in the free space. The algorithms can be divided into three categories: those that are working in configuration space(C-Space)(C- Space is the set of all possible joint angles of a robotic arm) , the mixed approaches using both Cartesian and C-Space and those that are using only the Cartesian space. Although Cartesian space seems more appropriate, due to dimensionality, this work illustrates that the C-Space planners can achieve comparable or better results. Initially an enhanced approach for efficient collision detection in C-Space, used by the planners, is presented. Afterwards the N dimensional cuboid region, notated as Rq, is defined. The Rq configures the C-Space so that the sampling is done close to a selected, called center, cell. The approach is enhanced by the decomposition of the Cartesian space into cells. A cell is selected appropriately if: (a) is closer to the target position and (b) lies inside the constraints. Inverse kinematics(IK) are applied to calculate a centre configuration used later by the Rq. The CellBiRRT is proposed and combines all the features. Continuously mixed approaches that do not require goal configuration or an analytic solution of IK are presented. Rq regions as well as Cells are also integrated in these approaches. A Cartesian sampling based planner using quaternions for linear interpolation is also proposed and tested. The common feature of the so far algorithms is the feasibility which is normally against the optimality. Therefore an additional part of this work deals with the optimality of the path. An enhanced approach of CellBiRRT, called CellBiRRT*, is developed and promises to compute shorter paths in a reasonable time. An on-line method using both CellBiRRT and CellBiRRT* is proposed where the path of the robot arm is improved and recalculated even if sudden changes in the environment are detected. Benchmarking with the state of the art algorithms show the good performance of the proposed approaches. The good performance makes the algorithms suitable for real time applications. In this work several applications are described: Manipulative skills, an approach for an semi-autonomous control of the robot arm and a motion planning library. The motion planning library provides the necessary interface for easy use and further development of the motion planning algorithms. It can be used as the part connecting the manipulative skill designing and the motion of a robotic arm

    A generalized laser simulator algorithm for optimal path planning in constraints environment

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    Path planning plays a vital role in autonomous mobile robot navigation, and it has thus become one of the most studied areas in robotics. Path planning refers to a robot's search for a collision-free and optimal path from a start point to a predefined goal position in a given environment. This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. This approach allows finding the path for a mobile robot while avoiding obstacles, searching for a goal, considering some constraints and finding an optimal path during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating a wave of points in all directions towards the goal point with adhering to constraints. A simulation study employing the proposed approach is applied to the grid map settings to determine a collision-free path from the start to goal positions. First, the grid mapping of the robot's workspace environment is constructed, and then the borders of the workspace environment are detected based on the new proposed function. This function guides the robot to move toward the desired goal. Two concepts have been implemented to find the best candidate point to move next: minimum distance to goal and maximum index distance to the boundary, integrated by negative probability to sort out the most preferred point for the robot trajectory determination. In order to construct an optimal collision-free path, an optimization step was included to find out the minimum distance within the candidate points that have been determined by GLS while adhering to particular constraint's rules and avoiding obstacles. The proposed algorithm will switch its working pattern based on the goal minimum and boundary maximum index distances. For static obstacle avoidance, the boundaries of the obstacle(s) are considered borders of the environment. However, the algorithm detects obstacles as a new border in dynamic obstacles once it occurs in front of the GLS waves. The proposed method has been tested in several test environments with different degrees of complexity. Twenty different arbitrary environments are categorized into four: Simple, complex, narrow, and maze, with five test environments in each. The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. The GLS is 7.8 and 5.5 times faster than A* and LS, respectively, generating a path 1.2 and 1.5 times shorter than A* and LS. The mean value of the path cost achieved by the proposed approach is 4% and 15% lower than PRM and RRT, respectively. The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. Finally, to verify the performance of the developed method for generating a collision-free path, experimental studies were carried out using an existing WMR platform in labs and roads. The experimental work investigates complete autonomous WMR path planning in the lab and road environments using live video streaming. The local maps were built using data from live video streaming s by real-time image processing to detect the segments of the lab and road environments. The image processing includes several operations to apply GLS on the prepared local map. The proposed algorithm generates the path within the prepared local map to find the path between start-to-goal positions to avoid obstacles and adhere to constraints. The experimental test shows that the proposed method can generate the shortest path and best smooth trajectory from start to goal points in comparison with the laser simulator

    A methodology to determine the functional workspace of a 6R robot using forward kinematics and geometrical methods

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    The work envelope of a robot does not capture the effect of tool orientation. Applications will require the tool to be at a certain orientation to perform the tasks necessary. It is therefore important to introduce a parameter that can capture the effect of orientation for multiple robots and configurations. This is called the functional work space, which is a subset of the work envelope would capture the effect of orientation. This research discusses the development of establishing an assessment tool that can predict the functional work space of a robot for a certain tool-orientation pair thus aiding in proper tool, tool path, fixture, related configuration selection and placement. Several solutions are studied and an analytical and a geometric solution is presented after a detailed study of joint dependencies, joint movements, limits, link lengths and displacements through visual, empirical and analytical approaches. The functional workspace curve for a manipulator with similar kinematic structure can be created using the geometrical solution discussed in this research. It is difficult to derive a general paradigm since different parameters such as, joint limits, angles and twist angles seem to have a different effect on the shape of the workspace. The geometrical solution employed is simple, easy to deduce and can be simulated with a commercial software package. Design decisions pertaining to configuration and reconfiguration of manipulators will benefit by employing the solution as a design/analysis tool. A case study involving an X-ray diffraction technique goniometer is presented to highlight the merits of this work

    Task Partitioning for Distributed Assembly

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    This thesis addresses the problem of how to plan a strategy for a team of robots to cooperatively build a structure, henceforth referred to as the distributed assembly problem. The problem of distributed assembly requires a range of capabilities for successful completion of the task. These include accurate sensing and manipulation using a mobile robot, the ability to continuously adhere to precedence constraints on placements, and the ability to guarantee static stability at every stage of construction. The fundamental contribution of this work is to propose methods to address task allocation problems in the presence of constraints on task ordering. Algorithms are presented to partition 2- and 3-D assembly tasks into separate subtasks that satisfy local and global precedence constraints between the assembly components. The objective is to achieve a partitioning that minimizes completion time by minimizing the workload imbalance between the robots, and maximizes assembly parallelization. Towards this objective four approaches are presented. The first is an approach where each robot runs a simultaneous Dijkstra's Algorithm with its own root. The second approach incorporates online workload balancing and error correction by adding a communication scheme and a scanning robot equipped with a visual depth sensor. The third approach addresses the task partitioning using an algorithm inspired by Ant Colony Optimization. Finally, the problem of cooperative manipulation for tasks that require close coordination is addressed. All approaches are tested in both simulation and experiment.Ph.D., Mechanical Engineering -- Drexel University, 201
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