Path Planning in Complex Environments for Industrial Robots with Additional Degrees of Freedom

Author(s):  
Francisco Valero ◽  
Vicente Mata ◽  
Marco Ceccarelli
Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1960
Author(s):  
Azade Fotouhi ◽  
Ming Ding ◽  
Mahbub Hassan

In this paper, we address the application of the flying Drone Base Stations (DBS) in order to improve the network performance. Given the high degrees of freedom of a DBS, it can change its position and adapt its trajectory according to the users movements and the target environment. A two-hop communication model, between an end-user and a macrocell through a DBS, is studied in this work. We propose Q-learning and Deep Q-learning based solutions to optimize the drone’s trajectory. Simulation results show that, by employing our proposed models, the drone can autonomously fly and adapts its mobility according to the users’ movements. Additionally, the Deep Q-learning model outperforms the Q-learning model and can be applied in more complex environments.


Author(s):  
Danming Wei ◽  
Alireza Tofangchi ◽  
Andriy Sherehiy ◽  
Mohammad Hossein Saadatzi ◽  
Moath Alqatamin ◽  
...  

Abstract Industrial robots, as mature and high-efficient equipment, have been applied to various fields, such as vehicle manufacturing, product packaging, painting, welding, and medical surgery. Most industrial robots are only operating in their own workspace, in other words, they are floor-mounted at the fixed locations. Just some industrial robots are wall-mounted on one linear rail based on the applications. Sometimes, industrial robots are ceiling-mounted on an X-Y gantry to perform upside-down manipulation tasks. The main objective of this paper is to describe the NeXus, a custom robotic system that has been designed for precision microsystem integration tasks with such a gantry. The system tasks include assembly, bonding, and 3D printing of sensor arrays, solar cells, and microrobotic prototypes. The NeXus consists of a custom designed frame, providing structural rigidity, a large overhead X-Y gantry carrying a 6 degrees of freedom industrial robot, and several other precision positioners and processes. We focus here on the design and precision evaluation of the overhead ceiling-mounted industrial robot of NeXus and its supporting frame. We first simulated the behavior of the frame using Finite Element Analysis (FEA), then experimentally evaluated the pose repeatability of the robot end-effector using three different types of sensors. Results verify that the performance objectives of the design are achieved.


2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840079
Author(s):  
Wensheng Huang ◽  
Hongli Xu

The application of machine vision to industrial robots is a hot topic in robot research nowadays. A welding robot with machine vision had been developed, which is convenient and flexible to reach the welding point with six degrees-of-freedom (DOF) manipulator, while the singularity of its movement trail is prevented, and the stability of the mechanism had been fully guaranteed. As the precise industry camera can capture the optical feature of the workpiece to reflect in the camera’s CCD lens, the workpiece is identified and located through a visual pattern recognition algorithm based on gray scale processing, on the gradient direction of edge pixel or on geometric element so that high-speed visual acquisition, image preprocessing, feature extraction and recognition, target location are integrated and hardware processing power is improved. Another task is to plan control strategy of control system, and the upper computer software is programmed in order that multi-axis motion trajectory is optimized and servo control is accomplished. Finally, prototype was developed and validation experiments show that the welding robot has high stability, high efficiency, high precision, even if welding joints are random and workpiece contour is irregular.


2021 ◽  
Vol 8 ◽  
Author(s):  
Zubair Iqbal ◽  
Maria Pozzi ◽  
Domenico Prattichizzo ◽  
Gionata Salvietti

Collaborative robots promise to add flexibility to production cells thanks to the fact that they can work not only close to humans but also with humans. The possibility of a direct physical interaction between humans and robots allows to perform operations that were inconceivable with industrial robots. Collaborative soft grippers have been recently introduced to extend this possibility beyond the robot end-effector, making humans able to directly act on robotic hands. In this work, we propose to exploit collaborative grippers in a novel paradigm in which these devices can be easily attached and detached from the robot arm and used also independently from it. This is possible only with self-powered hands, that are still quite uncommon in the market. In the presented paradigm not only hands can be attached/detached to/from the robot end-effector as if they were simple tools, but they can also remain active and fully functional after detachment. This ensures all the advantages brought in by tool changers, that allow for quick and possibly automatic tool exchange at the robot end-effector, but also gives the possibility of using the hand capabilities and degrees of freedom without the need of an arm or of external power supplies. In this paper, the concept of detachable robotic grippers is introduced and demonstrated through two illustrative tasks conducted with a new tool changer designed for collaborative grippers. The novel tool changer embeds electromagnets that are used to add safety during attach/detach operations. The activation of the electromagnets is controlled through a wearable interface capable of providing tactile feedback. The usability of the system is confirmed by the evaluations of 12 users.


2021 ◽  
pp. 1-16
Author(s):  
Zhaojun Zhang ◽  
Rui Lu ◽  
Minglong Zhao ◽  
Shengyang Luan ◽  
Ming Bu

The research of path planning method based on genetic algorithm (GA) for the mobile robot has received much attention in recent years. GA, as one evolutionary computation model, mimics the process of natural evolution and genetics. The quality of the initial population plays an essential role in improving the performance of GA. However, when GA based on a random initialization method is applied to path planning problems, it will lead to the emergence of infeasible solutions and reduce the performance of the algorithm. A novel GA with a hybrid initialization method, termed NGA, is proposed to solve this problem in this paper. In the initial population, NGA first randomly selects three free grids as intermediate nodes. Then, a part of the population uses a random initialization method to obtain the complete path. The other part of the population obtains the complete path using a greedy-related method. Finally, according to the actual situation, the redundant nodes or duplicate paths in the path are deleted to avoid the redundant paths. In addition, the deletion operation and the reverse operation are also introduced to the NGA iteration process to prevent the algorithm from falling into the local optimum. Simulation experiments are carried out with other algorithms to verify the effectiveness of the NGA. Simulation results show that NGA is superior to other algorithms in convergence accuracy, optimization ability, and success rate. Besides, NGA can generate the optimal feasible paths in complex environments.


2020 ◽  
Vol 10 (5) ◽  
pp. 1721
Author(s):  
Petar Ćurković ◽  
Lovro Čehulić

Path planning is present in many areas, such as robotics, video games, and unmanned autonomous vehicles. In the case of robots, it is a primary low-level prerequisite for the successful execution of high-level tasks. It is a known and difficult problem to solve, especially in terms of finding optimal paths for robots working in complex environments. Recently, population-based methods for multi-objective optimization, i.e., swarm and evolutionary algorithms successfully perform on different path planning problems. Knowing the nature of the problem is hard for optimization algorithms, it is expected that population-based algorithms might benefit from some kind of diversity maintenance implementation. However, advantages and potential traps of implementing specific diversity maintenance methods into the evolutionary path planner have not been clearly spelled out and experimentally demonstrated. In this paper, we fill this gap and compare three diversity maintenance methods and their impact on the evolutionary planner for problems of different complexity. Crowding, fitness sharing, and novelty search are tailored to fit specific problems, implemented, and tested for two scenarios: mobile robot operating in a 2D maze, and 3 degrees of freedom (DOF) robot operating in a 3D environment including obstacles. Results indicate that the novelty search outperforms the other two methods for problem domains of higher complexity.


Robotica ◽  
2009 ◽  
Vol 28 (4) ◽  
pp. 477-491 ◽  
Author(s):  
Shital S. Chiddarwar ◽  
N. Ramesh Babu

SUMMARYIn this paper, a decoupled offline path planning approach for determining the collision-free path of end effectors of multiple robots involved in coordinated manipulation is proposed. The proposed approach for decoupled path planning is a two-phase approach in which the path for coordinated manipulation is generated with a coupled interaction between collision checking and path planning techniques. Collision checking is done by modelling the links and environment of robot using swept sphere volume technique and utilizing minimum distance heuristic for interference check. While determining the path of the end effector of robots involved in coordinated manipulation, the obstacles present in the workspace are considered as static obstacles and the links of the robots are viewed as dynamic obstacles by the other robot. Coordination is done in offline mode by implementing replanning strategy which adopts incremental A* algorithm for searching the collision-free path. The effectiveness of proposed decoupled approach is demonstrated by considering two examples having multiple six degrees of freedom robots operating in 3D work cell environment with certain static obstacles.


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