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A basic motion planning problem is to compute a continuous path that connects a start configuration S and a goal configuration G, while avoiding collision with known obstacles. The robot and obstacle geometry is described in a 2D or 3D workspace , while the motion is represented as a path in (possibly higher-dimensional) configuration space .
Real-Time Path Planning is a term used in robotics that consists of motion planning methods that can adapt to real time changes in the environment. This includes everything from primitive algorithms that stop a robot when it approaches an obstacle to more complex algorithms that continuously takes in information from the surroundings and creates a plan to avoid obstacles.
Planning Alternative Tomorrows with Hope (PATH) is a strengths-based person-centred planning process developed by John O'Brien, Marsha Forest and Jack Pearpoint.The PATH process is designed to help a focus person establish their own vision for their life and imagine what supports and connections will help them achieve this vision.
Example of Multi-Agent Path Finding in a grid environment. The problem of Multi-Agent Pathfinding (MAPF) is an instance of multi-agent planning and consists in the computation of collision-free paths for a group of agents from their location to an assigned target.
Depending on the configuration, open-chain robotic manipulators require a degree of trajectory optimization. For instance, a robotic arm with 7 joints and 7 links (7-DOF) is a redundant system where one cartesian position of an end-effector can correspond to an infinite number of joint angle positions, thus this redundancy can be used to optimize a trajectory to, for example, avoid any ...
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The most basic form of Bug algorithm (Bug 1) is as follows: The robot moves towards the goal until an obstacle is encountered. Follow a canonical direction (clockwise) until the robot reaches the location of initial encounter with the obstacle (in short, walking around the obstacle).