Integration of perception, global planning and local planning in the manufacturing domain

2009 ◽  
Author(s):  
Christoph Ertelt ◽  
Kristina Shea ◽  
Dejan Pangercic ◽  
Thomas Ruhr ◽  
Michael Beetz
Keyword(s):  
Local Planning ◽  
Global Planning

Recent Advances in Robot Trajectory Planning in a Dynamic Environment

2021 ◽  
Vol 14 ◽  
Author(s):  
Hongxin Zhang ◽  
Rongzijun Shu ◽  
Guangsen Li
Keyword(s):  
Trajectory Planning ◽  
Dynamic Environment ◽  
Local Planning ◽  
Robot Trajectory ◽  
Recent Advances ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Task Collaboration ◽  
Global Planning ◽  
Robot Trajectory Planning

Background: Trajectory planning is important to research in robotics. As the application environment changes rapidly, robot trajectory planning in a static environment can no longer meet actual needs. Therefore, a lot of research has turned to robot trajectory planning in a dynamic environment. Objective: This paper aims at providing references for researchers from related fields by reviewing recent advances in robot trajectory planning in a dynamic environment. Methods: This paper reviews the latest patents and current representative articles related to robot trajectory planning in a dynamic environment and introduces some key methods of references from the aspects of algorithm, innovation and principle. Results: In this paper, we classified the researches related to robot trajectory planning in a dynamic environment in the last 10 years, introduced and analyzed the advantages of different algorithms in these patents and articles, and the future developments and potential problems in this field are discussed. Conclusion: Trajectory planning in a dynamic environment can help robots to accomplish tasks in a complex environment, improving robots’ intelligence, work efficiency and adaptability to the environment. Current research focuses on dynamic obstacle avoidance, parameter optimization, real-time planning, and efficient work, which can be used to solve robot trajectory planning in a dynamic environment. In terms of the combination of multiple algorithms, multi-sensor information fusion, the combination of local planning and global planning, and multi-robot and multi-task collaboration, more improvements and innovations are needed. It should create more patents on robot trajectory planning in a dynamic environment.

scholarly journals SISTEM NAVIGASI MOBILE ROBOT DALAM RUANGAN BERBASIS AUTONOMOUS NAVIGATION

2019 ◽  
Vol 4 (2) ◽  
pp. 78 ◽  
Author(s):  
Dwiky Erlangga ◽  
Endang D ◽  
Rosalia H S ◽  
Sunarto Sunarto ◽  
Kuat Rahardjo T.S ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Local Planning ◽  
Localization And Mapping ◽  
Monte Carlo Localization ◽  
Computer Based ◽  
Slam Algorithm ◽  
Main Components ◽  
Window Approach ◽  
Global Planning

<p><em>Autonomous navigation is absolutely necessary in mobile-robotic, which consists of four main components, namely: perception, localization, path-planning, and motion-control. Mobile robots create maps of space so that they can carry out commands to move from one place to another using the autonomous-navigation method. Map making using the Simultaneous-Localization-and-Mapping (SLAM) algorithm that processes data from the RGB-D camera sensor and bumper converted to laser-scan and point-cloud is used to obtain perception. While the wheel-encoder and gyroscope are used to obtain odometry data which is used to construct travel maps with the SLAM algorithm, gmapping and performing autonomous navigation. The system consists of three sub-systems, namely: sensors as inputs, single-board computers for processes, and actuators as movers. Autonomous-navigation is regulated through the navigation-stack using the Adaptive-Monte-Carlo-Localization (AMCL) algorithm for localization and global-planning, while the Dynamic-Window-Approach (DWA) algorithm with Robot-Operating-System-(ROS) for local -planning. The results of the test show the system can provide depth-data that is converted to laser-scan, bumper data, and odometry data to single-board-computer-based ROS so that mobile-controlled teleoperating robots from workstations can build 2-dimensional grid maps with total accuracy error rate of 0.987%. By using maps, data from sensors, and odometry the mobile-robot can perform autonomous-navigation consistently and be able to do path-replanning, avoid static obstacles and continue to do localization to reach the destination point.</em></p>

scholarly journals Mathematical modeling of the trajectory of a ship as a control object in local planning

2021 ◽  
Vol 339 ◽  
pp. 01015
Author(s):  
Oleksandr Kupraty
Keyword(s):  
Control Object ◽  
Water Area ◽  
Control Device ◽  
Local Planning ◽  
Operating Modes ◽  
Vibration Sensors ◽  
Global Planning ◽  
The Given ◽  
Rudder Angle ◽  
Sector Method

In the article proposes the decomposition of the global planning task in local planning. It is proposed to combine the segment method and the sector method of division of the circle to construct the ship’s trajectory in local planning. Corrective coefficients were selected for the correct geometry of the turning trajectory, combining the segment method and the sector method of constructing the ship’s trajectory. The article uses formulas of spherical trigonometry; the trajectory of the turn depends on the rudder angle, which in turn depends on the turning ability of the vessel under the given conditions. In determining the value of the angle of the rudder, the control device must take into account the ship’s turning ability in the conditions set, the value of the angle of the turn and the constrained water area. The combination of all factors allows to differentiate the ship’s turning ability such as: high HG, middle MD or low LW with regard to passage area. The ME shifting operating modes matrix proposed in the article works as a filter of modes of operation and is completely dependent on the readings of pressure, temperature and vibration sensors. The ship’s trajectory is constructed using calculations in MS Excel and graphic simulations in the MATLAB environment.

scholarly journals Rollover-Free Path Planning for Off-Road Autonomous Driving

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 614
Author(s):  
Xingyu Li ◽  
Bo Tang ◽  
John Ball ◽  
Matthew Doude ◽  
Daniel W. Carruth
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Autonomous Driving ◽  
Planning Method ◽  
Local Planning ◽  
Planning Stage ◽  
Local Path Planning ◽  
Global Route ◽  
Local Path ◽  
Global Planning

Perception, planning, and control are three enabling technologies to achieve autonomy in autonomous driving. In particular, planning provides vehicles with a safe and collision-free path towards their destinations, accounting for vehicle dynamics, maneuvering capabilities in the presence of obstacles, traffic rules, and road boundaries. Existing path planning algorithms can be divided into two stages: global planning and local planning. In the global planning stage, global routes and the vehicle states are determined from a digital map and the localization system. In the local planning stage, a local path can be achieved based on a global route and surrounding information obtained from sensors such as cameras and LiDARs. In this paper, we present a new local path planning method, which incorporates a vehicle’s time-to-rollover model for off-road autonomous driving on different road profiles for a given predefined global route. The proposed local path planning algorithm uses a 3D occupancy grid and generates a series of 3D path candidates in the s-p coordinate system. The optimal path is then selected considering the total cost of safety, including obstacle avoidance, vehicle rollover prevention, and comfortability in terms of path smoothness and continuity with road unevenness. The simulation results demonstrate the effectiveness of the proposed path planning method for various types of roads, indicating its wide practical applications to off-road autonomous driving.

Path Planning for Mobile Robot Based on Autoregressive Model

2013 ◽  
Vol 431 ◽  
pp. 269-274
Author(s):  
Chuang Feng Huai ◽  
Xue Yan Jia
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Autoregressive Model ◽  
Planning Process ◽  
Local Planning ◽  
Uncertain Environment ◽  
Motion Trajectories ◽  
Moving Obstacles ◽  
Global Planning

Proposed an uncertain environment path planning method for mobile robot in the presence of moving obstacles. Combining the global planning with the local planning, this dissertation presents a new approach to on-line real-time path planning with respect to the dynamic uncertain environment. With current sampling position, the autoregressive model predicts motion trajectories of moving obstacles. And the predicted positions are treated as instantaneously static. So moving obstacles in the predicted positions can be considered as static in the path planning process. Simulation examples demonstrated the effectiveness, feasibility, real-time capability, high stability and perfect performance of obstacle avoidance.

scholarly journals Research on an Obstacle Avoidance Method for UAV

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhenqi He ◽  
Lu Yao
Keyword(s):  
Kalman Filter ◽  
Obstacle Avoidance ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
Local Planning ◽  
Living Body ◽  
Sigma Point ◽  
Local Path ◽  
Global Planning ◽  
Local Programming

With the continuous development of UAV technology, UAV has been widely used in various industries. In the flight process of UAV, UAV often changes the given path because of obstacles (including static nonliving body and moving living body). According to the properties of obstacles and the characteristics of UAV, standard Kalman filter is used for nonmaneuvering targets, and sigma point Kalman filter is used for maneuvering targets. In the aspect of obstacle avoidance, the minimum search method is used to get the initial population of local programming. Then, the improved genetic algorithm is run. Combined with the predicted obstacle features, the local planning path can be obtained. Finally, the local planning path and global planning path are combined to generate the planning path with new obstacles. At the end of the paper, the obstacle avoidance strategies of static and moving obstacles are simulated. The simulation results show that this method has fast convergence speed and good feasibility and can flexibly deal with the obstacle avoidance and local path planning of various new obstacles.

scholarly journals Towards Goal-Directed Navigation Through Combining Learning Based Global and Local Planners

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 176 ◽  
Author(s):  
Xiaomao Zhou ◽  
Yanbin Gao ◽  
Lianwu Guan
Keyword(s):  
Reinforcement Learning ◽  
Navigation System ◽  
Fundamental Problem ◽  
Robot Navigation ◽  
Great Success ◽  
Navigation Systems ◽  
Local Planning ◽  
End To End ◽  
Global Planning ◽  
Global And Local

Robot navigation is a fundamental problem in robotics and various approaches have been developed to cope with this problem. Despite the great success of previous approaches, learning-based methods are receiving growing interest in the research community. They have shown great efficiency in solving navigation tasks and offer considerable promise to build intelligent navigation systems. This paper presents a goal-directed robot navigation system that integrates global planning based on goal-directed end-to-end learning and local planning based on reinforcement learning (RL). The proposed system aims to navigate the robot to desired goal positions while also being adaptive to changes in the environment. The global planner is trained to imitate an expert’s navigation between different positions by goal-directed end-to-end learning, where both the goal representations and local observations are incorporated to generate actions. However, it is trained in a supervised fashion and is weak in dealing with changes in the environment. To solve this problem, a local planner based on deep reinforcement learning (DRL) is designed. The local planner is first implemented in a simulator and then transferred to the real world. It works complementarily to deal with situations that have not been met during training the global planner and is able to generalize over different situations. The experimental results on a robot platform demonstrate the effectiveness of the proposed navigation system.

Social mobilization and tackling the performance of local government in rural Nepal

2020 ◽  
Author(s):  
Ganesh Prasad Pandeya ◽  
Tatsuo Oyama ◽  
Chakrapani Acharya
Keyword(s):  
Local Government ◽  
Citizen Participation ◽  
Social Mobilization ◽  
Power Dynamics ◽  
Local Power ◽  
Local Planning ◽  
Rural Villages ◽  
Disadvantaged Groups ◽  
Participatory Institutions ◽  
Rural Nepal

Abstract Based on extensive fieldwork in two rural villages, this paper qualitatively examines how social mobilization initiatives influence local government (LG) performance in Nepal. LG mobilized community people to empower them for their effective participation in local planning and decision-making processes. Comparing with the prior period of mobilization, evidence demonstrates that mobilization promises to boost LG performance through empowering communities to enhance their agency and entitlements, promoting democratic and effective citizen participation, and strengthening LG responsiveness and social accountability. But these connections are not straightforward, as there appeared discrepancies in parallel in recognizing equal participation rights of disadvantaged groups and equitable distribution of public resources among social groups. The findings imply that mobilization can be an effective strategy for tackling many challenges of participatory institutions, as it tends to create social pressures for making participatory institutions more democratic and changing the local power dynamics in favour of disadvantaged groups.

scholarly journals ‘We need to put what we do in my dad’s language, in pounds, shillings and pence’: Commercialisation and the reshaping of public-sector planning in England

Urban Studies ◽  
2021 ◽  
pp. 004209802198995
Author(s):  
Jason Slade ◽  
Malcolm Tait ◽  
Andy Inch
Keyword(s):  
Public Sector ◽  
Built Environment ◽  
Ethnographic Study ◽  
Professional Identities ◽  
Local Planning ◽  
Planning Practice ◽  
Neoliberal Governance ◽  
Original Contribution ◽  
Disciplinary Matrix ◽  
Planning Authority

This article furthers understanding of how commercial imperatives are reshaping dominant conceptions of planning practice in England, and by extension the production of the built environment more widely. We make an original contribution by tracing the emergence of the logic of commercialisation in England, demonstrating how the impacts of austerity and ‘market-led viability planning’ have entrenched the ‘delivery state’, a powerful disciplinary matrix representing late-neoliberal governance. Through in-depth, ethnographic study of a local planning authority, we argue that commercialisation within the delivery state creates a distinct ‘economy of attention’, reshaping planners’ agency and professional identities, and the substance and scope of their work. The conclusion draws out wider implications of commercialisation for planning in and beyond the delivery state.

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