scholarly journals A Robot-Centered Path-Planning Algorithm for Multidirectional Additive Manufacturing for WAAM Processes and Pure Object Manipulation

2021 ◽  
Vol 11 (13) ◽  
pp. 5759
Author(s):  
Markus Schmitz ◽  
Jan Wiartalla ◽  
Markus Gelfgren ◽  
Samuel Mann ◽  
Burkhard Corves ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Path Planning ◽  
Critical Path ◽  
Object Manipulation ◽  
Robot Kinematics ◽  
Planning Algorithm ◽  
Path Planner ◽  
Joint Velocity ◽  
Path Planning Algorithm ◽  
Wire Arc Additive Manufacturing

Previous algorithms for slicing, path planning or trajectory planning of additive manufacturing cannot be used consistently for multidirectional additive manufacturing with pure object manipulation in wire-arc additive manufacturing. This work presents a novel path planning approach that directly takes robot kinematics into account and thus ensures the reachability of all critical path poses. In an additional step, the planned path segments are smoothed so that joint velocity limits are respected. It is shown that the implemented path planner generates executable robot paths and at the same time maintains the process quality (in this case, sufficient coverage of the slice area). While the introduced method enables the generation of reachable printing paths, the smoothing algorithm allows for the execution of the path with respect to the robot’s velocity limits and at the same time improves the slice coverage. Future experiments will show the realization of the real robot setup presented.

scholarly journals Intelligent Beetle Antennae Search for UAV Sensing and Avoidance of Obstacles

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1758 ◽  
Author(s):  
Qing Wu ◽  
Xudong Shen ◽  
Yuanzhe Jin ◽  
Zeyu Chen ◽  
Shuai Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Heuristic Algorithm ◽  
Heuristic Algorithms ◽  
Search Range ◽  
Turning Angle ◽  
Planning Algorithm ◽  
Search Speed ◽  
Path Planner ◽  
Path Planning Algorithm

Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.

scholarly journals Obstacle Avoidance Path Planning for Worm-like Robot Using Bézier Curve

Biomimetics ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 57
Author(s):  
Yifan Wang ◽  
Zehao Liu ◽  
Akhil Kandhari ◽  
Kathryn A. Daltorio
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Optimization Techniques ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Planning Optimization ◽  
Planning Algorithm ◽  
Lateral Clearance ◽  
Path Planner ◽  
Path Planning Algorithm

Worm-like robots have demonstrated great potential in navigating through environments requiring body shape deformation. Some examples include navigating within a network of pipes, crawling through rubble for search and rescue operations, and medical applications such as endoscopy and colonoscopy. In this work, we developed path planning optimization techniques and obstacle avoidance algorithms for the peristaltic method of locomotion of worm-like robots. Based on our previous path generation study using a modified rapidly exploring random tree (RRT), we have further introduced the Bézier curve to allow more path optimization flexibility. Using Bézier curves, the path planner can explore more areas and gain more flexibility to make the path smoother. We have calculated the obstacle avoidance limitations during turning tests for a six-segment robot with the developed path planning algorithm. Based on the results of our robot simulation, we determined a safe turning clearance distance with a six-body diameter between the robot and the obstacles. When the clearance is less than this value, additional methods such as backward locomotion may need to be applied for paths with high obstacle offset. Furthermore, for a worm-like robot, the paths of subsequent segments will be slightly different than the path of the head segment. Here, we show that as the number of segments increases, the differences between the head path and tail path increase, necessitating greater lateral clearance margins.

Automated Planning for Robotic Multi-Resolution Additive Manufacturing

2021 ◽  
pp. 1-18
Author(s):  
Prahar Bhatt ◽  
Ashish Kulkarni ◽  
Rishi K. Malhan ◽  
Brual Shah ◽  
Yeo Jung Yoon ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Path Planning ◽  
Surface Quality ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
Material Extrusion ◽  
Material Deposition ◽  
Build Time ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Abstract Conventional material extrusion additive manufacturing (AM) processes require the user to make a trade-off between surface quality and build time of the part. The use of a large bead filament deposition can speed up the build process; however, it leads to surfaces with high roughness due to the stair-stepping effect. The surface quality can be improved by using a small bead filament deposition, which in turn increases the build time of the part. We present a new approach incorporating hybrid multi-resolution layers in material extrusion additive manufacturing to provide excellent surface quality without increasing the build time. Our slicing algorithm generates planar layers with large filament to fill the interior regions in less time. The generated exterior layers are conformal and use small filament to reduce the stair-stepping effect and improve surface quality. We also present a path planning algorithm to build parts with a single manipulator using a multi-nozzle extrusion tool. The path planning algorithm generates a smooth material deposition path by avoiding collision between the tool and the already built layers. It reduces the collision checks and performs collision detection in a computationally efficient manner. We build five parts to validate our approach and illustrate the benefits of multi-resolution AM.

scholarly journals Reinforcement Learning Path Planning Method with Error Estimation

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 247
Author(s):  
Feihu Zhang ◽  
Can Wang ◽  
Chensheng Cheng ◽  
Dianyu Yang ◽  
Guang Pan
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Error Estimation ◽  
Autonomous Driving ◽  
Planning Method ◽  
Robot Kinematics ◽  
Learning Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Accumulated Error

Path planning is often considered as an important task in autonomous driving applications. Current planning method only concerns the knowledge of robot kinematics, however, in GPS denied environments, the robot odometry sensor often causes accumulated error. To address this problem, an improved path planning algorithm is proposed based on reinforcement learning method, which also calculates the characteristics of the cumulated error during the planning procedure. The cumulative error path is calculated by the map with convex target processing, while modifying the algorithm reward and punishment parameters based on the error estimation strategy. To verify the proposed approach, simulation experiments exhibited that the algorithm effectively avoid the error drift in path planning.

Path Planning for Autonomous Car Parking

2018 ◽  
Author(s):  
Letian Lin ◽  
J. Jim Zhu
Keyword(s):  
Path Planning ◽  
Target Line ◽  
Planning Problem ◽  
Control Laws ◽  
Computational Costs ◽  
Planning Algorithm ◽  
Path Planner ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
Reverse Path

The path planning problem for autonomous car parking has been widely studied. However, it is challenging to design a path planner that can cope with parking in tight environment for all common parking scenarios. The important practical concerns in design, including low computational costs and little human’s knowledge and intervention, make the problem even more difficult. In this work, a path planner is developed using a novel four-phase algorithm. By using some switching control laws to drive two virtual cars to a target line, a forward path and a reverse path are obtained. Then the two paths are connected along the target line. As illustrated by the simulation results, the proposed path planning algorithm is fast, highly autonomous, sufficiently general and can be used in tight environment.

scholarly journals Path Planning for Aircraft Fleet Launching on the Flight Deck of Carriers

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 175 ◽  
Author(s):  
Yongtao Li ◽  
Yu Wu ◽  
Xichao Su ◽  
Jingyu Song
Keyword(s):  
Path Planning ◽  
Collision Detection ◽  
Planning Problem ◽  
Aircraft Carrier ◽  
Planning Algorithm ◽  
Rolling Optimization ◽  
Path Planner ◽  
Path Planning Algorithm ◽  
Flight Deck ◽  
Path Planning Problem

This paper studies the path planning problem for aircraft fleet taxiing on the flight deck of carriers, which is of great significance for improving the safety and efficiency level of launching. As there are various defects of manual command in the flight deck operation of carriers, the establishment of an automatic path planner for aircraft fleets is imperative. The requirements of launching, the particularities of the flight deck environment, the way of launch, and the work mode of catapult were analyzed. On this basis, a mathematical model was established which contains the constraints of maneuverability and the work mode of catapults; the ground motion and collision detection of aircraft are also taken into account. In the design of path planning algorithm, path tracking was combined with path planning, and the strategy of rolling optimization was applied to get the actual taxi path of each aircraft. Taking the Nimitz-class aircraft carrier as an example, the taxi paths of aircraft fleet launching was planned with the proposed method. This research can guarantee that the aircraft fleet complete launching missions safely with reasonable taxi paths.

scholarly journals Bi-Directional Drone Design and its Path Planning

2021 ◽  
Vol 10 (3) ◽  
pp. 71-74
Author(s):  
Soutrik Mukherjee ◽  
Keyword(s):  
Path Planning ◽  
Weight Ratio ◽  
Processing System ◽  
Mathematical Induction ◽  
Problem Statement ◽  
Weight Category ◽  
Memory Processing ◽  
Planning Algorithm ◽  
Path Planner ◽  
Path Planning Algorithm

There are two aspects to my project, one is optimized bi-directional drone designing and other is its path planning. The optimization in design lies in the fact that my drone can carry load both in +z and –z axis if its direction of motion is in x-y plane. This design optimization helps the drone to carry more payload than drones of same frame(basic chassis) weight category. In other words, my drone has greater payload to its own weight ratio(almost 0.8) than other drones with almost similar or same functionalities. Coming to path planning algorithm, I have taken a mathematical induction approach to solve the problem statement by clearly defining our conditions to follow to remain in the specified path along with constraints lying in the path. My goal as a path planner has to ensure that the drone follows the conditions specified without grappling into obstacles. Also, to achieve the desired goal in least possible time. The paths traversed by the drone would be stored into the memory processing system of the drone for future development of algorithm.

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