Autonomous Landing at Unprepared Sites for a Cargo Unmanned Air System
Agency / Branch:
DOD / NAVY
We propose to design, develop, implement, simulate, and demonstrate an autonomous control and sensing system for the safe vertical landing of autonomous aerial cargo delivery system (ACDS). The landing site is expected to be unprepared mountain sides with slopes up to 15 degrees and rough terrain containing rocks and brush. We also plan to reduce the amount of ground equipment required to operate the system, overall weight and power requirements of the control and sensing system, and estimate probability of hard landing. During Phase I we will develop two approaches for sensing systems using FMCW radar and 3D Flash Ladar in selecting the landing site from a distance of 75 m and estimate the cost, weight, volume, computing requirement for processing raw sensor data and running control algorithms, and the total power needed for sensors and computers. We will also simulate the control and sensing algorithms on the RIPTIDE environment using the vehicle dynamics model of Yamaha RMAX and Boeing's A160T. We will develop metrics to evaluate the performance of the control algorithms and sensing approaches and provide an initial set of results using the simulation environment. During Phase II we will perform a detailed implementation of the control algorithms and sensing approaches. We will simulate performance using 6-degree of freedom models for RMAX and Boeing's A160T and tune the control algorithm and sensing approaches. At the end of Phase II we will do a demonstration of landing using the RMAX on a hill side.
Small Business Information at Submission:
Research Institution Information:
Data Flux Systems Inc.
986 Cragmont Ave Berkeley, CA 94708
Number of Employees:
University of California
2108 Allston Way
Berkeley, CA 94704