An Optimization-Based Planner with B-spline Parameterized Continuous-Time Reference Signals

For the cascaded planning and control modules implemented for robot navigation, the frequency gap between the planner and controller has received limited attention. In this study, we introduce a novel B-spline parameterized optimization-based planner (BSPOP) designed to address the frequency gap challenge with limited onboard computational power in robots. The proposed planner generates continuous-time control inputs for low-level controllers running at arbitrary frequencies to track. Furthermore, when considering the convex control action sets, BSPOP uses the convex hull property to automatically constrain the continuous-time control inputs within the convex set. Consequently, compared with the discrete-time optimization-based planners, BSPOP reduces the number of decision variables and inequality constraints, which improves computational efficiency as a byproduct. Simulation results demonstrate that our approach can achieve a comparable planning performance to the high-frequency baseline optimization-based planners while demanding less computational power. Both simulation and experiment results show that the proposed method performs better in planning compared with baseline planners in the same frequency.

Authors

• Chuyuan Tao
• Sheng Cheng 0001
• Fanxin Wang
• Yang Zhao
• Naira Hovakimyan

Keywords

• Convex hulls
• Navigation
• Simulation
• Linear programming
• Planning
• Computational efficiency
• Splines (mathematics)
• Optimization
• Frequency control
• Intelligent robots
• Optimization-based Planners
• Active Control
• Power Calculation
• Control Input
• Decision Variables
• Inequality Constraints
• Convex Set
• Frequent Interruptions
• Low-level Control
• Robot Navigation
• Continuous-time Control
• Optimization Problem
• Objective Function
• Computation Time
• Optimal Control
• Control Signal
• Angular Velocity
• Control Points
• Autonomous Vehicles
• Control Constraints
• Increase In Computation Time
• Number Of Optimization Variables
• Constrained Optimization
• Optimal Control Input
• Basis Matrix
• B-spline Basis Functions
• Optimization Variables
• Feasible Set
• Longer Computation Time