Glosarium AI
Kamus lengkap Kecerdasan Buatan
Inverse Kinematics
Mathematical method for calculating the joint configurations of a robot to reach a specified position and orientation of the end effector. It is fundamental for motion planning in manipulator robotics.
Configuration Space
Set of all possible positions and orientations that a robot can reach, represented as a multidimensional space where each dimension corresponds to a degree of freedom. Trajectory planning is performed in this abstract space.
Adaptive Control
Control strategy that automatically adjusts its parameters based on variations in the system or environment, ensuring robust performance in the face of modeled uncertainties. It is particularly useful for robots operating in dynamic environments.
Extended Kalman Filter
Recursive estimation algorithm for nonlinear systems that linearizes models around the current state to estimate the robot's position and velocity. It is widely used in robotic navigation and localization.
RRT Planning
Trajectory planning algorithm based on random exploration of the configuration space, building a tree of states to quickly find a feasible path. It excels in high-dimensional spaces with numerous obstacles.
Predictive Control
Control method that uses a dynamic model to predict the future behavior of the system and optimizes a sequence of commands over a sliding horizon. It is particularly suited for systems with state and control constraints.
Workspace
Three-dimensional volume that a robot's end effector can reach, determined by the geometric and kinematic limits of the manipulator. It is crucial for task planning and robotic cell design.
Inverse Dynamics
Calculation of the torques or forces required to produce a desired acceleration of the robot, taking into account its mass, inertia, and dynamic effects. It is essential for precise control of high-speed movements.
Sliding Mode Control
Robust nonlinear control technique that forces the system's trajectory to slide along a predefined surface toward equilibrium, ensuring rapid convergence and insensitivity to disturbances. It is particularly effective for robotic systems.
Collocation Optimization
Method for solving optimal control problems that discretizes state and control variables at collocation points to transform the continuous problem into nonlinear optimization. It allows generating complex optimal trajectories.
Hierarchical Control
Control architecture organized into multiple decision levels, from strategic planning level to tactical trajectory tracking level. It enables managing the complexity of autonomous robotic behaviors.
Reactive Navigation
Control strategy based on local rules making immediate decisions according to current sensory information, without global planning. It allows rapid responsiveness to environmental changes.
Nonlinear Control
Theory and practice of control for systems whose dynamic equations are not linear, including manipulator and mobile robots. It uses techniques like feedback linearization and differential geometry.
Dynamic Obstacle Avoidance
Capability of a robotic system to modify its trajectory in real-time to avoid moving obstacles, using predictive algorithms and adaptive potential fields. It is crucial for robot-human coexistence.
Trajectory Tracking
Control problem consisting of converging a robot's movement toward a predefined space-time reference trajectory, minimizing tracking error. It uses state feedback and predictive control techniques.
H-infinity Robust Control
Control design methodology guaranteeing system stability and performance in the face of bounded uncertainties in H-infinity norm. It is particularly suited for robotic applications requiring high reliability.
Optimized Motion Generation
Algorithmic process for synthesizing robotic trajectories that minimize performance criteria such as energy, time, or mechanical wear while respecting kinematic and dynamic constraints. It combines numerical optimization and physical constraints.