Robust Collision Avoidance via Sliding Control

• Main Authors: Lopez, Brett T. (Author), Slotine, Jean-Jacques E (Author), How, Jonathan P. (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Aerospace Controls Laboratory (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2020-04-14T14:56:47Z.
• Subjects: Article
• Online Access: Get fulltext

Recent advances in perception and planning algorithms have enabled robots to navigate autonomously through unknown, cluttered environments at high-speeds. A key component of these systems is the ability to identify, select, and execute a safe trajectory around obstacles. Many of these systems, however, lack performance guarantees because model uncertainty and external disturbances are ignored when a trajectory is selected for execution. This work leverages results from nonlinear control theory to establish a bound on tracking performance that can be used to select a provably safe trajectory. The Composite Adaptive Sliding Controller (CASC) provides robustness to disturbances and reduces model uncertainty through high-rate parameter estimation. CASC is demonstrated in simulation and hardware to significantly improve the performance of a quadrotor navigating through unknown environments with external disturbances and unknown model parameters. Keywords: Trajectory; Electron tubes; Uncertainty; Robustness; Optimization; Adaptation models
National Science Foundation Graduate Research Fellowship (Grant No. 1122374)
DARPA Fast Lightweight Autonomy (FLA) Program.