scholarly journals Online 3-Dimensional Path Planning with Kinematic Constraints in Unknown Environments Using Hybrid A* with Tree Pruning

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1152
Author(s):  
Jonatan Scharff Willners ◽  
Daniel Gonzalez-Adell ◽  
Juan David Hernández ◽  
Èric Pairet ◽  
Yvan Petillot
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Search Tree ◽  
Planning Time ◽  
3 Dimensional ◽  
Unknown Environments ◽  
Current Path ◽  
Planning Algorithm ◽  
Path Planner ◽  
Tree Pruning

In this paper we present an extension to the hybrid A* (HA*) path planner. This extension allows autonomous underwater vehicle (AUVs) to plan paths in 3-dimensional (3D) environments. The proposed approach enables the robot to operate in a safe manner by accounting for the vehicle’s motion constraints, thus avoiding collisions and ensuring that the calculated paths are feasible. Secondly, we propose an improvement for operations in unexplored or partially known environments by endowing the planner with a tree pruning procedure, which maintains a valid and feasible search-tree during operation. When the robot senses new obstacles in the environment that invalidate its current path, the planner prunes the tree of branches which collides with the environment. The path planning algorithm is then initialised with the pruned tree, enabling it to find a solution in a lower time than replanning from scratch. We present results obtained through simulation which show that HA* performs better in known underwater environments than compared algorithms in regards to planning time, path length and success rate. For unknown environments, we show that the tree pruning procedure reduces the total planning time needed in a variety of environments compared to running the full planning algorithm during replanning.

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

scholarly journals Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics

2021 ◽  
Author(s):  
Jie Zhong ◽  
Tao Wang ◽  
Lianglun Cheng
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Free Path ◽  
Inverse Kinematics ◽  
Multiple Dimensions ◽  
Continuous State ◽  
Planning Algorithm ◽  
Convergence Performance ◽  
Path Planner ◽  
Action Spaces

AbstractIn actual welding scenarios, an effective path planner is needed to find a collision-free path in the configuration space for the welding manipulator with obstacles around. However, as a state-of-the-art method, the sampling-based planner only satisfies the probability completeness and its computational complexity is sensitive with state dimension. In this paper, we propose a path planner for welding manipulators based on deep reinforcement learning for solving path planning problems in high-dimensional continuous state and action spaces. Compared with the sampling-based method, it is more robust and is less sensitive with state dimension. In detail, to improve the learning efficiency, we introduce the inverse kinematics module to provide prior knowledge while a gain module is also designed to avoid the local optimal policy, we integrate them into the training algorithm. To evaluate our proposed planning algorithm in multiple dimensions, we conducted multiple sets of path planning experiments for welding manipulators. The results show that our method not only improves the convergence performance but also is superior in terms of optimality and robustness of planning compared with most other planning algorithms.

scholarly journals Real - Time Trajectory and Velocity Planning for Autonomous Vehicles

2021 ◽  
Vol 10 (5) ◽  
pp. 439-448
Author(s):  
Hrishikesh Dey ◽  
Rithika Ranadive ◽  
Abhishek Chaudhari
Keyword(s):  
Path Planning ◽  
Velocity Profile ◽  
Real Time ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Autonomous Driving ◽  
Navigation Algorithm ◽  
Velocity Planning ◽  
Planning Algorithm ◽  
Path Planner

Path planning algorithm integrated with a velocity profile generation-based navigation system is one of the most important aspects of an autonomous driving system. In this paper, a real-time path planning solution to obtain a feasible and collision-free trajectory is proposed for navigating an autonomous car on a virtual highway. This is achieved by designing the navigation algorithm to incorporate a path planner for finding the optimal path, and a velocity planning algorithm for ensuring a safe and comfortable motion along the obtained path. The navigation algorithm was validated on the Unity 3D Highway-Simulated Environment for practical driving while maintaining velocity and acceleration constraints. The autonomous vehicle drives at the maximum specified velocity until interrupted by vehicular traffic, whereas then, the path planner, based on the various constraints provided by the simulator using µWebSockets, decides to either decelerate the vehicle or shift to a more secure lane. Subsequently, a splinebased trajectory generation for this path results in continuous and smooth trajectories. The velocity planner employs an analytical method based on trapezoidal velocity profile to generate velocities for the vehicle traveling along the precomputed path. To provide smooth control, an s-like trapezoidal profile is considered that uses a cubic spline for generating velocities for the ramp-up and ramp-down portions of the curve. The acceleration and velocity constraints, which are derived from road limitations and physical systems, are explicitly considered. Depending upon these constraints and higher module requirements (e.g., maintaining velocity, and stopping), an appropriate segment of the velocity profile is deployed. The motion profiles for all the use-cases are generated and verified graphically.

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.

Research on Logistics Distribution Path Planning Algorithm Based on GIS

2014 ◽  
Vol 513-517 ◽  
pp. 1871-1874
Author(s):  
Tian Yang Su ◽  
Da Shen Xue
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Path Selection ◽  
Logistics Industry ◽  
Mountain Climbing ◽  
Logistics Distribution ◽  
Advantages And Disadvantages ◽  
Current Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Algorithm of vehicle scheduling optimization could be integrated in the GIS platform. Therefore, distribution software can automatically make the delivery plan and managers also can make the optimizing choice of the optimal distribution route. Firstly, this paper introduces the necessity of introducing GIS into the logistics industry. Moreover, advantages and disadvantages of the current path planning in the logistics distribution which often used in some algorithms (genetic algorithm, mountain climbing algorithm, ant colony algorithm, etc.) will be listed. Finally, a more practical hybrid algorithm will be used to the GIS so that managers can optimize the logistics distribution path selection.

A Novel Path Planning Algorithm for Autonomous Underwater Vehicle

2013 ◽  
Vol 446-447 ◽  
pp. 1271-1278
Author(s):  
Bo Yin ◽  
Bing Liu ◽  
Jing Cao
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Moving Simulation ◽  
Path Planning Algorithm

A path planning algorithm based on sector scanning for AUV was proposed in this paper. By reducing the frequency of the calculation of the path planning, this method solved the problem that AUV can not respond to the frequent control instructions of path planning because of AUV’s poor flexibility. Meanwhile, by making the path more clear and reliable, the algorithm improved the operability of responding to the path planning results and operating the controlling of AUV’s moving. Simulation results show that this method is feasible and efficient.

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.

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