Configuration space is a crucial concept in motion planning, representing all feasible assignments to robot state, start, and goal states. It can have the same dimensionality as the robot state and can have higher or lower dimensionality than the workspace. A configuration is a complete specification of the position of every point in the system, and for a robot with k total motion DOFs, C-space is a coordinate system with one dimension per DOF. In C-space, a robot pose is simply a point-mass and all other points are represented by sampling based algorithms.
Most motion planning problems are PSPACE-hard, and the best deterministic algorithm known has a running time that is exponential in the dimension. Based on the notion of configuration space, the motion planning problem in 3D workspace can be reduced to path planning for a point robot in C-space. This method presents a configuration space (C-space)-based path-planning approach for a 2-DOF planar robotic arm.
A path planner is required to generate a collision-free path between an initial and goal configuration. The configuration space is an important foundation to understand when beginning to talk about motion planning problems. A configuration, q, is a mathematical concept that maps obstacles into the robot’s C-Space and creates regions of C-Space that contain obstacles and free-space. Path planners need only consider those obstacles that lie in the configuration space curve when required.
Optimality is achieved when a planning algorithm returns a path with the shortest length J∗ among all possible paths from start to goal. Once the configuration space is clearly understood, many motion planning problems that appear different in terms of geometry and kinematics can be solved by the proposed methods.
📹 Configuration Space or C-Space in Robotics for Robot Path planning by Bharat Dwivedi
In this video, Our summer Intern, Bharat Dwivedi presents the idea of Configuration space or C-Space for Autonomous robot path …
What are the informations needed in planning A route?
Route planning involves determining the destination, considering factors such as distance, time, road conditions, traffic, costs, route constraints, and safety. It is crucial for business owners and independent drivers to consider these factors to optimize routes and save time and money. Poorly planned routes often fail to consider essential factors such as vehicle type, maximum speed, traffic patterns, and specific travel hours.
Effective route planning can help individuals and businesses achieve their objectives more efficiently, saving time and money. This blog provides a comprehensive guide to understanding route planning and its potential benefits.
What is space configuration in architecture?
Spatial configurations are the arrangement and organization of objects or elements within a space, affecting its use and perception. They are crucial in architecture, as they ensure functionality and aesthetics by arranging and interconnecting different spaces within a structure. A good spatial configuration allows for efficient movement and use of space while maintaining an aesthetically pleasing environment. Understanding and implementing spatial configurations is essential for creating a functional and visually appealing environment in a building or structure.
What is the task space and configuration space?
A 4-degree of freedom SCARA robot arm has an end effector pose described by X, Y, Z, and a yaw angle. Its task space is a subset of r cubed, the set of all possible positions and orientations. Its configuration space is a four-dimensional quantity, comprising three rotational joint angles and a vertical displacement of the tool.
A 4-degree of freedom parallel link robot has a four-dimensional task space, controlling the position and orientation of the end effector. It has a four-dimensional configuration space with four motors connected by links to the end effector. The four joint educational robot has a four-dimensional task space and configuration due to its four rotational joints.
For a 6-degree of freedom arm, the task space is a subset of SE3, the set of all possible positions in three-dimensional space and the set of all possible orientations in three-dimensional space. All these robots have six joints or 6 degrees of freedom. The industrial robot and the space shuttle arm have six rotational joints, while the Stanford arm has five rotational joints and one sliding joint.
The configuration space for a redundant robot is a subset of the 100-dimensional space of real numbers, which is greater than the dimension of the task space. This allows the tool-tip to achieve any position and orientation like a 6-degree of freedom industrial robot, but also control the shape of the arm. An industrial robot with only six joints can only control the pose of the end effector and cannot choose an arbitrary configurational shape of its arm.
What are the requirements for path planning?
Path planning is a process that helps autonomous vehicles or robots find the shortest and most obstacle-free path from a start to goal state. It requires a map of the environment, including start and goal states, and can be represented in grid maps, state spaces, and topological roadmaps. Popular path planning algorithms include grid-based search algorithms, which find a path based on minimum travel cost in a grid map, sampling-based search algorithms, which create a searchable tree by randomly sampling new nodes or robot configurations in a state space, and trajectory optimization algorithms, which formulate the path planning problem as an optimization problem considering desired vehicle performance, relevant constraints, and vehicle dynamics. These algorithms can be applied for online path planning in uncertain environments but may be prohibitive due to the complexity of the optimization problem.
What is the difference between configuration item and baseline?
A Configuration Item (CI) is a specific item, like a registry key or file, while a Configuration Baseline (BASE) is made up of one or more CIs. The more CIs added, the more items are evaluated together, and if one CI is in an error state, the whole baseline will be in an error state. A CI cannot be deployed, while a baseline cannot be deployed without a CI. To create a new baseline, right-click on Configuration Baselines in the SCCM Current Branch console, select “Create Configuration Baseline”, and choose “Configuration Items” from the drop-down menu.
Is joint space the same as configuration space?
The joint space, or configuration space, represents the location of all robot links and is determined by the joint variables, q ∈ ℜ N. This space is used for text and data mining, AI training, and similar technologies. Cookies are used by this site, and all rights are reserved, including those for text and data mining, AI training, and similar technologies. Creative Commons licensing terms apply for open access content.
What are the essential planning requirements?
A good project plan is crucial for success in project management. It outlines business justification, stakeholder needs, requirements, objectives, scope statement, deliverables, estimated due dates, detailed project schedule, risk assessment, management plan, and defined roles and responsibilities. The article shares ten key ingredients to create a perfect plan, ensuring smooth team and project operations.
An infographic is provided to summarize these elements, providing a visual representation of the essential elements. By implementing these elements, a project can avoid scope creep, overblown budgets, missed deadlines, and stress, ultimately leading to a more successful outcome.
What is a path configuration?
A ‘Configuration Path’ is the path followed by configuration information within a system or network device, determining how settings are applied and managed. It helps in determining routing protocols and network configurations. ScienceDirect uses cookies and all rights are reserved for text and data mining, AI training, and similar technologies. Open access content is licensed under Creative Commons terms.
What is configuration space in path planning?
The configuration space (C) indicates whether a possible configuration is collision-prone and non-navigable or collision-free and navigable. The site uses cookies and requires continued use. Copyright © 2024 Elsevier B. V., its licensors, and contributors. All rights reserved for text and data mining, AI training, and similar technologies. Creative Commons licensing terms apply for open access content.
What is the difference between state space and configuration space?
The state space and configuration space are two distinct objects in fluid dynamics. The state space represents probabilities acting on the phase space, while the configuration space represents all possible positions. In fluid dynamics, flow velocity components can be expressed as the derivative of a scalar stream function, which is analogous to Hamilton’s equation. This similarity was discovered in the 1980s, providing a new direction in the field.
What is the concept of configuration space?
In classical mechanics, generalized coordinates define the configuration of a system, which is then represented by the configuration space of the physical system. This space is often mathematically constrained, resulting in a manifold called the configuration manifold of the system. This is an “unrestricted” configuration space, where different point particles can occupy the same position. In mathematics, particularly topology, a “restricted” configuration space is commonly used, with diagonals removed to represent “colliding” particles.
A single particle’s position in Euclidean 3-space is defined by the vector, and its configuration space is the vector. The symbol for a point in configuration space is used to denote momenta, while the symbol refers to velocities.
A particle may be constrained to move on a specific manifold, such as a sphere, where its configuration space is the subset of coordinates that define points on the sphere. In this case, the manifold is the sphere.
📹 Efficient Configuration Space Representation in Path Planning
UCLA Computational Robotics 209AS final presentation by Akhil Avula, Aidan Cookson, Calvin Change, and Daniel Truong.
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