Robot navigation with model predictive equilibrium point control

An autonomous vehicle intended to carry passengers must be able to generate trajectories on-line that are safe, smooth and comfortable. Here, we propose a strategy for robot navigation in a structured, dynamic indoor environment, where the robot reasons about the near future and makes a locally optimal decision at each time step.

Authors

• Jong Jin Park
• Collin Johnson
• Benjamin Kuipers

Keywords

• Robots
• Collision avoidance
• Trajectory
• Navigation
• Optimization
• Aerospace electronics
• Dynamics
• Equilibrium Point
• Predictive Control
• Model Predictive Control
• Robot Navigation
• Time Step
• Optimization Problem
• Dynamic Environment
• Local Optimum
• Indoor Environments
• Autonomous Vehicles
• Unconstrained Optimization Problem
• Continuous Optimization Problems
• Low-dimensional Problems
• Model Predictive Control Framework
• Cost Function
• Optimal Control
• Feedback Control
• Parametrized
• Multiple Objects
• Optimization Framework
• Linear Velocity
• Robot Motion
• Rapidly-exploring Random Tree
• Static Environment
• Dynamic Obstacles
• Dynamic Objects
• Planning Cycle
• Navigation Function
• Navigation Problem
• Target Pose