แนวคิดหลัก
A motion planning methodology based on Control Barrier Functions (CBF) and Signal Temporal Logic (STL) is employed to enable task completion within specified time intervals, considering a dynamic system subject to velocity constraints, while introducing an angular constraint to maintain the user within the robot's field of view (FOV) for enhanced human-robot interaction.
บทคัดย่อ
The paper presents a CBF-based STL motion planning approach for Socially Responsible Navigation (SRN) in crowded environments. The key highlights are:
The methodology allows for task completion within specified time intervals, while considering velocity constraints and obstacle avoidance.
An angular constraint is introduced to maintain the user within the robot's field of view (FOV), enhancing human-robot interaction and enabling a side-by-side human-robot companion.
The angular constraint is formulated as a separate CBF component, which is integrated into the optimization problem to ensure the user remains in the robot's FOV.
Simulation results demonstrate the effectiveness of the approach in adhering to spatio-temporal constraints, including velocity, rotation, and obstacle avoidance.
The authors mention future work on integrating prediction methods to enable the robot to adjust its motion based on the behavior of the person being accompanied.