Efficient Trajectory Library Filtering for Quadrotor Flight in Unknown Environments

Quadrotor flight in cluttered, unknown environments is challenging due to the limited range of perception sensors, challenging obstacles, and limited onboard computation. In this work, we directly address these challenges by proposing an efficient, reactive planning approach. We introduce the Bitwise Trajectory Elimination (BiTE) algorithm for efficiently filtering out in-collision trajectories from a trajectory library by using bitwise operations. Then, we outline a full receding-horizon planning approach for quadrotor flight in unknown environments demonstrated at up to 50 Hz on an onboard computer. This approach is evaluated extensively in simulation and shown to collision check up to 4896 trajectories in under 20μs, which is the fastest collision checking time for a MAV planner, to the best of the authors' knowledge. Finally, we validate our planner in over 120 minutes of flights in forest-like and urban subterranean environments.

Authors

• Vaibhav K. Viswanathan
• Eric Dexheimer
• Guanrui Li
• Giuseppe Loianno
• Michael Kaess
• Sebastian A. Scherer

Keywords

• Filtering
• Forestry
• Libraries
• Trajectory
• Planning
• Sensors
• Intelligent robots
• Unknown Environment
• Urban Environments
• Planning Approach
• Collision Detection
• Onboard Computer
• Bitwise Operations
• Micro Air Vehicles
• Multi-core
• Velocity Profile
• Sensor Measurements
• Depth Camera
• Size Of Map
• Map Representation
• Single Trajectory
• Trajectories In Space
• Mapping Step
• Scrolling
• Dimensional Map
• Occupancy Grid
• Collision-free Trajectory
• Motion Primitives
• Overview Of Trials
• Speckle Filtering
• Intel RealSense