With the emergence of Industry 4.0, high productivity is critically dependent on robot manipulators. However, building an efficient and safe work environment with robot manipulators remains a ...challenge of hardware capability. The optimal path planning of the robot manipulator usually encounters shortcomings in low computational speed and tedious training after changing assembly lines and increases the risk during human–robot collaboration (HRC). To solve such a problem, we propose a path planning, named slice-based heuristic fast marching tree, based on joint space to achieve real-time path planning speed without modeling or training the workspace in advance. Our experimental results indicate that the time consumed for path planning in static environments is only from 0.51 s to 1.63 s, tested by a 6-DOF general-purpose industrial manipulator and different cylindrical obstacle placements. The time for path replanning in dynamic environments is from 0.62 s to 0.88 s.
•Path planning is in 1.63 s with static obstacles and 0.88 s with dynamic obstacles.•The proposed path planning is faster, smoother, and shorter than RRT, RRT*, and FMT*.•The joint angles of revolutions in total are less than RRT, RRT*, FMT*.
Distributed robotic systems rely heavily on the publish–subscribe communication paradigm and middleware frameworks that support it, such as the Robot Operating System (ROS), to efficiently implement ...modular computation graphs. The ROS 2 executor, a high-level task scheduler which handles ROS 2 messages, is a performance bottleneck. We extend ros2_tracing, a framework with instrumentation and tools for real-time tracing of ROS 2, with the analysis and visualization of the flow of messages across distributed ROS 2 systems. Our method detects one-to-many and many-to-many causal links between input and output messages, including indirect causal links through simple user-level annotations. We validate our method on both synthetic and real robotic systems, and demonstrate its low runtime overhead. Moreover, the underlying intermediate execution representation database can be further leveraged to extract additional metrics and high-level results. This can provide valuable timing and scheduling information to further study and improve the ROS 2 executor as well as optimize any ROS 2 system. The source code is available at: github.com/christophebedard/ros2-message-flow-analysis.
In this paper, we proposed a novel multi-robot collaborative exploration method to improve the efficiency and robustness of multi-robot exploration in unknown environments. Firstly, a novel frontier ...detection algorithm based on hybrid multi-strategy rapidly-exploring random tree (HMS-RRT) is proposed, which is composed of an adaptive incremental distance strategy, a subregion sampling strategy and a greedy frontier-based exploration strategy. To improve the frontier detection performance of the algorithm, we adopt the Voronoi diagram to continuously partition the explored region, and dynamically adjust the incremental distance according to the density of obstacles in the subregions. To avoid the algorithm is trapped in the local optimum, we use Gaussian distribution to calculate the sampling probability in each subregion, so that the algorithm tends to sample in the subregion with lower crowded level of nodes and cover the unexplored regions quickly. Secondly, we introduce the greedy frontier-based exploration strategy to explore all Voronoi polygons in turn and refine the search results, meanwhile, the centroid of each frontier region is extracted as the exploration target point. Then, a multi-robot task assignment strategy based on improved market mechanism is introduced to dynamically assign the exploration target points to each robot, and the map-merging algorithm is used in the exploration process to merge several local maps in real-time. Finally, an experimental testing platform is developed based on Robot Operating System (ROS) and a series of experiments are carried out. The results show that our method can improve the efficiency and reliability of multi-robot exploration in both the simulations and the prototype experiments.
The application of efficient path planning algorithms for two-wheeled Autonomous Mobile Robots (AMRs) in static environments with obstacles is a significant challenge in robotics research. Existing ...methods, such as the A star (A*) algorithm utilized in Robot Operating System 2 (ROS2), can provide optimal paths but may have high computational complexity in intricate environments. This study explores the potential of three metaheuristic algorithms - Improved Particle Swarm Optimization (IPSO), Improved Grey Wolf Optimizer (IGWO), and Artificial Bee Colony (ABC) - for planning efficient and smooth paths in static environments. These algorithms are selected due to their ability to efficiently find near-optimal solutions and avoid local minima. In this study, the researchers designed and built a two-wheeled AMR using a Raspberry Pi 4 microcontroller as the main processing unit, working in conjunction with an Arduino Mega for controlling the DC motor drive through an MDD10A motor driver circuit. The robot is equipped with an RPLiDAR A1 sensor to read 360-degree distance values for mapping and obstacle avoidance. The experimental results clearly indicate that the metaheuristic algorithms, especially ABC, can calculate paths up to 7% shorter than A* while requiring only one-tenth of the time. Moreover, ABC demonstrates superior motion smoothness when applied to the actual two-wheeled robot in static environments. This work represents a significant step in developing algorithms for two-wheeled robots that are ready to support real-world operations in industries, logistics, healthcare, or various service sectors, which can help increase efficiency and reduce operating costs in the future.
•Developed MAs for efficient path planning of AMRs in ROS 2.•Tested IPSO, IGWO, and ABC algorithms on a custom-built, two-wheeled AMR prototype.•ABC outperformed A* with up to 7% shorter paths and 90% faster computation times.•ABC demonstrated superior motion smoothness, facilitating navigation in complex environments.
Given the global population ages, the traditional medical system must change. Telemedicine combines the introduction of devices with sensors, software, and other Internet of Things technologies. ...Telemedicine is a new type of medical technology application. In this paper, we systematically integrate the force sensor, robot arm, optical radar device, and jelly mechanism to develop a telemedicine application system. We used a three-dimensional coordinate conversion formula to convert the coordinates of each axis of the robot arm into the coordinates of the smartphone so that the doctor can control the robot arm remotely using the smartphone. The force sensor embedded in the robot arm provides transparency to the doctor during operation, enabling them to monitor whether the force applied by the robotic arm on the human body is excessive. In addition, through the jelly mechanism installed on the robot arm, the doctor only needs to use a smartphone to control the jelly mechanism to achieve remote control needs. The experimental testing results sufficiently show the practicability of our scheme for telemedicine.
Energy consumption estimation and management of the maritime Unmanned Surface Vehicles (USV) is an important issue to deal with energy minimization techniques such as path planning, tasks scheduling, ...etc. In this paper, we introduce the energy consumption parameter in USV simulation through three contributions: 1) An analytic USV's energy consumption model is developed based on the three-degrees-of-freedom dynamic model of surface vessels. 2) A reverse engineering approach is proposed to identify the previously used dynamic model parameters based on a set of scenarios executed within a recent simulation environment. 3) The simulator engine is enriched with the consumption modelling tools such that the power absorbed by the USV is instantaneously calculated and returned; thus, the required energy of any predefined scenario is available as a new simulation result.
•The unmanned maritime drones' autonomy is limited by their battery capacities.•Several available approaches are used to reduce their consumption.•The existing solutions are not feasible in complicated environments or huge scenarios.•The problem is solved by developing a more realistic power model of the marine drones.•A robust simulator is used to manage and estimate the consumption of marine drones.
From its internal representation of a building, or, its building world, a robot can retrieve a building's information for task planning and execution. However, a building is a complex construct ...composed of thousands of sub-elements, therefore manually programming the complete lifecycle information in a robot can be impractical. Our study presents the creation of a semantic building world from a building information model (BIM) that can be used for robot operations. To describe static and dynamic elements, we create a Universal Robot Description Format (URDF) building world using the Industry Foundation Classes (IFC) that a robot can directly query information for task planning and execution. As the case study demonstrates, our study bridges the gap between BIM's lifecycle information and robot operations. By allowing robots to acquire information about operating environments, the proposed methodologies provide the foundation for studies attempting task robotization in different types of facilities throughout their lifecycles.
•Presented a framework that connects BIM and robot task planning and execution.•Generated a semantic URDF-based building world representation for robots.•Achieved enhanced description of static and dynamic elements of a building.•A robot retrieved building element information for task planning and execution.•Proposed BIM-robot integration, essential for robotization in built environments.
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