A Virtual Reality Interface for an Autonomous Spray Painting UAV

Vempati, Anurag Sai; Khurana, Harshit; Kabelka, Vojtech; Flueckiger, Simon; Siegwart, Roland; Beardsley, Paul

doi:10.1109/lra.2019.2922588

Cited by 24 publications

(13 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research has also focused on the development of gesture languages, as in the works of Soto-Gerrero and Ramrez-Torres ( 2016 ) and Couture et al ( 2018 ). Virtual reality is also becoming an increasingly popular technology, and is beginning to be applied to the control of MAVs (Tsykunov and Tsetserukou, 2019 ; Vempati et al, 2019 ). Besides the above, a less technical, yet highly significant, challenge to overcome on this front is the (understandably) stringent legislation surrounding MAV flight, particularly in outdoor scenarios, often requiring at least one pilot per drone (the specifics vary based on the location) (Vincenzi et al, 2015 ).…”

Section: Further Challenges and Future Developments To Be Madementioning

confidence: 99%

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

et al. 2020

View full text Add to dashboard Cite

This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing robotic systems, enabling behaviors ranging from basic relative collision avoidance to higher level coordination. This ability, at times taken for granted, also must be sufficiently reliable. Moreover, herein lies a constraint: the design choice of the relative localization sensor has a direct link to the behaviors that the swarm can (and should) perform. Vision-based systems, for instance, force MAVs to fly within the field of view of their camera. Range or communication-based solutions, alternatively, provide omni-directional relative localization, yet can be victim to unobservable conditions under certain flight behaviors, such as parallel flight, and require constant relative excitation. At the swarm level, the final outcome is thus intrinsically influenced by the on-board abilities and sensors of the individual. The real-world behavior and operations of an MAV swarm intrinsically follow in a bottom-up fashion as a result of the local level limitations in cognition, relative knowledge, communication, power, and safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm.

show abstract

Section: Further Challenges and Future Developments To Be Madementioning

confidence: 99%

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Vempati et al proposed using texture synthesis based on a probability model to render the 3D tree model. Yeh and Ming studied the automatic rendering method of the 3D animal model [13]. Shick et al proposed a fluid simulation method based on Lattice Boltzmann Equation to simulate ink diffusion [14].…”

Section: Related Workmentioning

confidence: 99%

Ink Art Three-Dimensional Big Data Three-Dimensional Display Index Prediction Model

Cao

2021

Complexity

View full text Add to dashboard Cite

This paper starts with the study of realistic three-dimensional models, from the two aspects of ink art style simulation model and three-dimensional display technology, explores the three-dimensional display model of three-dimensional model ink style, and conducts experiments through the software development platform and auxiliary software. The feasibility of the model is verified. Aiming at the problem of real-time rendering of large-scale 3D scenes in the model, efficient visibility rejection method and a multiresolution fast rendering method were designed to realize the rapid construction and rendering of ink art 3D virtual reality scenes in a big data environment. A two-dimensional cellular automaton is used to simulate a brushstroke model with ink and wash style, and outlines are drawn along the path of the brushstroke to obtain an effect close to the artistic style of ink and wash painting. Set the surface of the model with ink style brushstroke texture patterns, refer to the depth map, normal map, and curvature map information of the model, and simulate the drawing effect of the method by procedural texture mapping. Example verification shows that the rapid visualization analysis model of ink art big data designed in this paper is in line with the prediction requirements of ink art big data three-dimensional display indicators. The fast visibility removal method is used to deal with large-scale three-dimensional ink art in a big data environment. High efficiency is achieved in virtual reality scenes, and the multiresolution fast rendering method better maintains the appearance of the prediction model without major deformation.

show abstract

“…For example, a large furniture production line platform is quite expensive and requires a factory building to be set up. However, VR can reduce the training cost on the actual machine platform via simulation of a virtual machine platform and environment, as well as reduce the risk associated with some furniture production processes, such as the spray painting and coating line, which emit odors and have toxic chemical compositions (Vempati et al, 2019). With VR training, the risk of occupational injury is eliminated (García et al, 2016).…”

Section: Application Of Vr Technology In Furniture Woodworking Trainingmentioning

confidence: 99%

Applying virtual reality for learning woodworking in the vocational training of batch wood furniture production

Lee

2020

Interactive Learning Environments

View full text Add to dashboard Cite

Taiwan's vocational wood-furniture schools still focus only on the traditional manual training strategy, and so students' knowledge of the furniture-manufacturing process is fragmented. Moreover, they possess limited manual skills without learning the workflows and strategies of furniture production, which is inadequate for satisfying the direct work demands of the furniture industry overseas. In response, through virtual reality (VR) technology, this study employed simulations of the furniture production lines in a large Vietnamese furniture-manufacturing factory, enabling students to experience and observe the manufacturing process of furniture production through VR to overcome the limitations in the present teaching environment. In doing so, we recruited 29 freshmen majoring in a furniture-and-woodworking program and divided them into an experimental group (N=15) and a control group (N=14). They were trained with actual furniture production-process cases according to the furniture mass-production process, including paper-based tests, equipment configuration re-draws and production planning table writing. The results showed that the students in the experimental VR-training group had superior judgment concerning the concept of batch furniture production line. This indicates that applying VR technology to the vocational training of batch furniture production effectively enhanced the students' familiarity of the fast and dynamic production situation of furniture production lines.

show abstract

A Virtual Reality Interface for an Autonomous Spray Painting UAV

Cited by 24 publications

References 16 publications

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

Ink Art Three-Dimensional Big Data Three-Dimensional Display Index Prediction Model

Applying virtual reality for learning woodworking in the vocational training of batch wood furniture production

Contact Info

Product

Resources

About