A Real-Time Obstacle Detection and Reactive Path Planning System for Autonomous Small-Scale Helicopters

Abstract

This paper presents the design of a comprehensive Multi-layer Architecture for Trajectory Replanning and Intelligent eXecution (MATRIX) system and its evaluation through high-fidelity simulations of the R-50 helicopter in the Real-time Interactive Prototype Technology Integration/Development Environment (RIPTIDE). The main feature of the MATRIX system is that it assures effective real-time obstacle detection & avoidance in a cluttered environment. Specifically, this paper discusses the (i) Design of the MATRIX System; (ii) Design, implementation & testing of individual modules; (iii) Integration & implementation under RIPTIDE; and (iv) Study of the features and limitations of the proposed architecture and algorithms. The MATRIX system consists of several subsystems including: Path Planner based on Rapidly-exploring Random Trees (RRT), shortest path algorithm for pruning of redundant waypoints, a safety corridor for preventing collisions with obstacles, 4D trajectory generator, nonlinear adaptive outer-loop controller, representation of obstacles using Quadtrees, and obstacle detection using a scanning laser and Interacting Multiple Model Kalman Filters (IMM-KF). These subsystems were developed and integrated within RIPTIDE, and extensive testing was carried out using R-50 helicopter dynamics. It was found that the MATRIX system rapidly generates new paths and trajectories to avoid unknown obstacles, is highly robust, and achieves excellent overall performance.

Recent advances in unmanned aerial vehicles real-time trajectory planning

“…In our survey, we found 67 publications that explicitly claimed real-time achievements in UAV trajectory planning (Beard et al 2002;Zheng et al 2003;Kuwata and How 2004;Cocaud 2006;Weiss et al 2006;Wzorek and Doherty 2006;Ducard et al 2007;Redding et al 2007;Jung and Tsiotras 2008b;Kim et al 2008;Yang and Sukkarieh 2008;Allaire et al 2009;Guo et al 2009;Jung et al 2009;Kothari et al 2009 Sun et al 2015;Wen et al 2015;Yao et al 2015;Zejun et al 2015;Palossi et al 2016;Ramana et al 2016;Turnbull et al 2016;Yongbo et al 2016;Ten Harmsel et al 2017).…”

Highway design software as support of a project‐based learning course

“…However, the RRT planner is more appropriate for unknown environments, because it can build its road map online. There are also some other works on applying RRT methods to rotorcraft path planning, but only simulation results have been presented (Redding et al, 2007; Yang, Gan, & Sukkarieh, 2010).…”

Obstacle detection for visually impaired patients

“…Another system is designed with sun glass incorporated with two cameras that helps in capturing the image of an obstacle. The image captured is sent to a palmtop and a desktop computer [6]. A normal individual is asked to monitor the desktop computer and alerts the visually impaired about the position, depth and the accuracy of an obstacle through earphones [7].…”