Vision-based landing of a simulated unmanned aerial vehicle with fast reinforcement learning

Landing is one of the difficult challenges for an unmanned aerial vehicle (UAV). In this paper, we propose a vision-based landing approach for an autonomous UAV using reinforcement learning (RL). The autonomous UAV learns the landing skill from scratch by interacting with the environment. The reinforcement learning algorithm explored and extended in this study is Least-Squares Policy Iteration (LSPI) to gain a fast learning process and a smooth landing trajectory. The proposed approach has been tested with a simulated quadrocopter in an extended version of the USARSim Unified System for Automation and Robot Simulation) environment. Results showed that LSPI learned the landing skill very quickly, requiring less than 142 trials

An evaluation of post-production facial composite enhancement techniques

Purpose: This article describes four experiments evaluating post-production enhancement techniques with facial composites mainly created using the EFIT-V holistic system. Design/methodology/approach: Each experiment was conducted in two stages. In Stage 1, constructors created between one and four individual composites of unfamiliar targets. These were merged to create morphs, and in Experiment 3, composites were also vertically stretched. In Stage 2, participants familiar with the targets named or provided target-similarity ratings to the images. Findings: In Experiments 1-3, correct naming rates were significantly higher to between-witness 4-morphs, within-witness 4-morphs and vertically stretched composites than to individual composites. In Experiment 4, there was a positive relationship between composite-target similarity ratings and between-witness morph-size (2-, 4-, 8-, 16-morphs). Practical implications: The likelihood of a facial composite being recognised can be improved by morphing and vertical stretch. Originality/value: A greater understanding of the theoretical underpinnings and applied advantage of post-production facial composite techniques should ensure greater acceptance by the criminal justice system, leading to better detection outcomes