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  2. Motion planning - Wikipedia

    en.wikipedia.org/wiki/Motion_planning

    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 .

  3. Partial least squares path modeling - Wikipedia

    en.wikipedia.org/wiki/Partial_least_squares_path...

    The partial least squares path modeling or partial least squares structural equation modeling (PLS-PM, PLS-SEM) [1] [2] [3] is a method for structural equation modeling that allows estimation of complex cause-effect relationships in path models with latent variables.

  4. Real-time path planning - Wikipedia

    en.wikipedia.org/wiki/Real-time_path_planning

    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.

  5. Trajectory optimization - Wikipedia

    en.wikipedia.org/wiki/Trajectory_optimization

    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 ...

  6. Probabilistic roadmap - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_roadmap

    The probabilistic roadmap [1] planner is a motion planning algorithm in robotics, which solves the problem of determining a path between a starting configuration of the robot and a goal configuration while avoiding collisions. An example of a probabilistic random map algorithm exploring feasible paths around a number of polygonal obstacles

  7. Model predictive control - Wikipedia

    en.wikipedia.org/wiki/Model_predictive_control

    Only the first step of the control strategy is implemented, then the plant state is sampled again and the calculations are repeated starting from the new current state, yielding a new control and new predicted state path. The prediction horizon keeps being shifted forward and for this reason MPC is also called receding horizon control. Although ...

  8. Closed-loop controller - Wikipedia

    en.wikipedia.org/wiki/Closed-loop_controller

    The control action is the switching on/off of the boiler, but the controlled variable should be the building temperature, but is not because this is open-loop control of the boiler, which does not give closed-loop control of the temperature. In closed loop control, the control action from the controller is dependent on the process output.

  9. Feed forward (control) - Wikipedia

    en.wikipedia.org/wiki/Feed_forward_(control)

    A pure feed-forward system is different from a homeostatic control system, which has the function of keeping the body's internal environment 'steady' or in a 'prolonged steady state of readiness.' A homeostatic control system relies mainly on feedback (especially negative), in addition to the feedforward elements of the system.