Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras

Event cameras, i.e., the Dynamic and Active-pixel Vision Sensor (DAVIS) ones, capture the intensity changes in the scene and generates a stream of events in an asynchronous fashion. The output rate of such cameras can reach up to 10 million events per second in high dynamic environments. DAVIS cameras use novel vision sensors that mimic human eyes. Their attractive attributes, such as high output rate, High Dynamic Range (HDR), and high pixel bandwidth, make them an ideal solution for applications that require high-frequency tracking. Moreover, applications that operate in challenging lighting scenarios can exploit the high HDR of event cameras, i.e., 140 dB compared to 60 dB of traditional cameras. In this paper, a novel asynchronous corner tracking method is proposed that uses both events and intensity images captured by a DAVIS camera. The Harris algorithm is used to extract features, i.e., frame-corners from keyframes, i.e., intensity images. Afterward, a matching algorithm is used to extract event-corners from the stream of events. Events are solely used to perform asynchronous tracking until the next keyframe is captured. Neighboring events, within a window size of 5x5 pixels around the event-corner, are used to calculate the velocity and direction of extracted event-corners by fitting the 2D planar using a randomized Hough transform algorithm. Experimental evaluation showed that our approach is able to update the location of the extracted corners up to 100 times during the blind time of traditional cameras, i.e., between two consecutive intensity images.Comment: Accepted to 15th International Symposium on Visual Computing (ISVC2020

Autonomous Moving Target-Tracking for a UAV Quadcopter Based on Fuzzy-PI

Moving target-tracking is an attractive application for quadcopters and a very challenging, complicated field of research due to the complex dynamics of a quadcopter and the varying speed of the moving target with time. For this reason, various control algorithms have been developed to track a moving target using a camera. In this paper, a Fuzzy-PI controller is developed to adjust the parameters of the PI controller using the position and change of position data as input. The proposed controller is compared to a gain-scheduled PID controller instead of the typical PID controller. To verify the performance of the developed system and distinguish which one has better performance, several experiments of a quadcopter tracking a moving target are conducted under the varying speed of the moving target, indoor and outdoor and during day and night. The obtained results indicate that the proposed controller works well for tracking a moving target under different scenarios, especially during night

Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable as possible, necessitating a comparative study of the recent work in this important area. The paper provides a comprehensive review of collision avoidance strategies used for unmanned vehicles, with the main emphasis on unmanned aerial vehicles (UAV). It is an in-depth survey of different collision avoidance techniques that are categorically explained along with a comparative analysis of the considered approaches w.r.t. different scenarios and technical aspects. This also includes a discussion on the use of different types of sensors for collision avoidance in the context of UAVs

Energy-Efficient Formation Morphing for Collision Avoidance in a Swarm of Drones

Two important aspects in dealing with autonomous navigation of a swarm of drones are collision avoidance mechanism and formation control strategy; a possible competition between these two modes of operation may have negative implications for success and efficiency of the mission. This issue is exacerbated in the case of distributed formation control in leader-follower based swarms of drones since nodes concurrently decide and act through individual observation of neighbouring nodes' states and actions. To dynamically handle this duality of control, a plan of action for multi-priority control is required. In this paper, we propose a method for formation-collision co-awareness by adapting the thin-plate splines algorithm to minimize deformation of the swarm's formation while avoiding obstacles. Furthermore, we use a non-rigid mapping function to reduce the lag caused by such maneuvers. Simulation results show that the proposed methodology maintains the desired formation very closely in the presence of obstacles, while the response time and overall energy efficiency of the swarm is significantly improved in comparison with the existing methods where collision avoidance and formation control are only loosely coupled. Another important result of using non-rigid mapping is that the slowing down effect of obstacles on the overall speed of the swarm is significantly reduced, making our approach especially suitable for time critical missions

Body Matters:Exploration of the Human Body as a Resource for the Design of Technologies for Meditation

Much research on meditation has shown its significant benefits for wellbeing. In turn, there has been growing HCI interest for the design of novel interactive technologies intended to facilitate meditation in real-time. In many of these systems, physiological signals have been mapped onto creative audiovisual feedback, however, there has been limited attention to the experiential qualities of meditation and the specific role that the body may play in them. In this paper, we report on workshops with 24 experts exploring the bodily sensations that emerge during meditation. Through material speculation, participants shared their lived experience of meditation and identified key stages during which they may benefit from additional aid, often multimodal. Findings emphasize the importance of recreating mindful physical sensations during moments of mind-wandering; in particular for supporting the regulation of attention through a range of embodied metaphors and haptic feedback, tailored to key transitions in the meditation process

Gregariousness Does Not Vary with Geography, Developmental Stage, or Group Relatedness in Feeding Redheaded Pine Sawfly Larvae

Aggregations are widespread across the animal kingdom, yet the underlying proximate and ultimate causes are still largely unknown. An ideal system to investigate this simple, social behavior is the pine sawfly genus Neodiprion, which is experimentally tractable and exhibits interspecific variation in larval gregariousness. To assess intraspecific variation in this trait, we characterized aggregative tendency within a single widespread species, the redheaded pine sawfly (N. lecontei). To do so, we developed a quantitative assay in which we measured interindividual distances over a 90-min video. This assay revealed minimal behavioral differences: (1) between early-feeding and late-feeding larval instars, (2) among larvae derived from different latitudes, and (3) between groups composed of kin and those composed of nonkin. Together, these results suggest that, during the larval feeding period, the benefits individuals derive from aggregating outweigh the costs and that this cost-to-benefit ratio does not vary dramatically across space (geography) or ontogeny (developmental stage). In contrast to the feeding larvae, our assay revealed a striking reduction in gregariousness following the final larval molt in N. lecontei. We also found some intriguing interspecific variation: While N. lecontei and N. maurus feeding larvae exhibit significant aggregative tendencies, feeding N. compar larvae do not aggregate at all. These results set the stage for future work investigating the proximate and ultimate mechanisms underlying developmental and interspecific variation in larval gregariousness across Neodiprion

Exploring the importance of within-canopy spatial temperature variation on transpiration predictions

Models seldom consider the effect of leaf-level biochemical acclimation to temperature when scaling forest water use. Therefore, the dependence of transpiration on temperature acclimation was investigated at the within-crown scale in climatically contrasting genotypes of Acer rubrum L., cv. October Glory (OG) and Summer Red (SR). The effects of temperature acclimation on intracanopy gradients in transpiration over a range of realistic forest growth temperatures were also assessed by simulation. Physiological parameters were applied, with or without adjustment for temperature acclimation, to account for transpiration responses to growth temperature. Both types of parameterization were scaled up to stand transpiration (expressed per unit leaf area) with an individual tree model (MAESTRA) to assess how transpiration might be affected by spatial and temporal distributions of foliage properties. The MAESTRA model performed well, but its reproducibility was dependent on physiological parameters acclimated to daytime temperature. Concordance correlation coefficients between measured and predicted transpiration were higher (0.95 and 0.98 versus 0.87 and 0.96) when model parameters reflected acclimated growth temperature. In response to temperature increases, the southern genotype (SR) transpiration responded more than the northern (OG). Conditions of elevated long-term temperature acclimation further separate their transpiration differences. Results demonstrate the importance of accounting for leaf-level physiological adjustments that are sensitive to microclimate changes and the use of provenance-, ecotype-, and/or genotype-specific parameter sets, two components likely to improve the accuracy of site-level and ecosystem-level estimates of transpiration flux