Essays about: "MAVs"
Showing result 1 - 5 of 7 essays containing the word MAVs.
-
1. DRONAR: Obstacle echolocation using ego-noise
University essay from Linköpings universitet/Institutionen för systemteknikAbstract : You do not want your drone to crash. Therefore, safety systems should be put in place to prevent such an event, and obstacle avoidance is a major part of this. Today, the most successful techniques use cameras or light detection and ranging (LIDAR) to find and avoid obstacles; but to improve resiliency, multiple systems should be used. READ MORE
-
2. Rapidly-Exploring Random Trees for real-time combined Exploration andPath Planning
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : The use of micro aerial vehicles (MAV) for civilian use such as exploration and inspection of varying structures, equipment and areas have garnered some interest as of late. MAVs have the mobility and agility to traverse three dimensional space quickly and access hard to reach areas where other alternatives would struggle, but a flying platform such as a MAV comes with it’s own set of distinct problems. READ MORE
-
3. Autonomous Aerial Void Exploration
University essay from Luleå tekniska universitet/DatavetenskapAbstract : Deploying robots in unknown and complex areas for inspection tasks is becoming a real need for various application scenarios. Recently, there has been an increasing interest to develop and use autonomous aerial robots in environments such as urban voids and subterranean mine tunnels, aiming to decrease the human presence in dangerous or inaccessible areas. READ MORE
-
4. Monocular vision-based obstacle avoidance for Micro Aerial Vehicles
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : The Micro Aerial Vehicless (MAVs) are gaining attention in numerous applications asthese platforms are cheap and can do complex maneuvers. Moreover, most of the commer-cially available MAVs are equipped with a mono-camera. READ MORE
-
5. Towards Robust Localization : Deep Feature Extraction with Convolutional Neural Networks
University essay from Luleå tekniska universitet/Signaler och systemAbstract : The ability for autonomous robotics to localize themselves in the environment is crucial and tracking the change of features in the environment is key for visual based odometry and localization. When shifting into rough environments of dust, smoke and poor illumination as well as erratic movements common in MAVs however, that task becomes substantially more difficult. READ MORE