Histo-Planner: A Real-time Local Planner for MAVs Teleoperation based on Histogram of Obstacle Distribution

Motivated by teleoperation applications in cluttered environments with limited computational power, we propose a local planner that does not require the knowledge or construction of a global map of the obstacles. The proposed solution consists of a real-time trajectory planning algorithm that relies on the histogram of obstacle distribution and a planner manager that triggers different planning modes depending on obstacles location around the MA V . The proposed solution is validated, for a teleoperation application, with both simulations and indoor experiments. Benchmark comparisons based on a designed simulation platform are also provided. I. INTRODUCTION Micro aerial vehicles (MA Vs) are used in many applications, such as rescue search, forestry monitoring, infrastructure maintenance, aerial photography, etc. When the MA V operates in cluttered environments, obstacle avoidance is a major problem. Solutions to this problem are highly dependent on the type of environment, the available onboard sensors, the availability of a global map of the environment, and the available computational power. While solutions to this problem rely on both perception and planning/navigation aspects (the classical sense and avoid scenario), the present paper focuses on the navigation aspect. Many traditional navigation methods are summarized in detail in [1].