Unmanned aerial vehicles (UAVs) operate with large degrees of autonomy when executing tasks from ... more Unmanned aerial vehicles (UAVs) operate with large degrees of autonomy when executing tasks from a ground-based controller. In this work, we design an (immersive) interface for drone management. Our interface supports operators in mission execution of one or several (automated) UAVs within a fleet. This allows operators to assign tasks to UAVs, while safe operations are ensured through in-flight conflict detection and prevention. Our interface fulfills both functional (e.g., reliability) and non-functional requirements (e.g., perceived cognitive load during use). A key design challenge is the latency in information exchanges, which introduces information asymmetries between the humans and UAVs. We then validate the effectiveness of our interface design across several experiments. We find that our design reduces the perceived cognitive load and improves task performance. Altogether, this work has implications for designing interfaces in human-machine collaboration, so humans can effe...
Unmanned aerial vehicles (UAVs) are expected to provide a wide range of services, whereby UAV fle... more Unmanned aerial vehicles (UAVs) are expected to provide a wide range of services, whereby UAV fleets will be managed by several independent service providers in shared low-altitude airspace. One important element, or redundancy, for safe and efficient UAV operation is pre-flight Conflict Detection and Resolution (CDR) methods that generate conflict-free paths for UAVs before the actual flight. Multi-Agent Path Finding (MAPF) has already been successfully applied to comparable problems with ground robots. However, most MAPF methods were tested with simplifying assumptions which do not reflect important characteristics of many real-world domains, such as delivery by UAVs where heterogeneous agents need to be considered, and new requests for flight operations are received continuously. In this paper, we extend CBS and ECBS to efficiently incorporate heterogeneous agents with computational geometry and we reduce the search space with spatio-temporal pruning. Moreover, our work introduce...
In future UAV-based services, UAV fleets will be managed by independent service providers in shar... more In future UAV-based services, UAV fleets will be managed by independent service providers in shared low-altitude airspace. Therefore, Conflict Detection and Resolution (CDR) methods that solve conflicts, i.e. possible collisions, between UAVs of all service providers are a key element of the Unmanned Aircraft System Traffic Management (UTM) system. We present a top-to-bottom algorithmic system with an extension to UAV operations of ORCA, a state-of-the-art algorithm in robotics. Then, using extreme-conflict situations, we empirically determine optimal parameter values for our adapted ORCA, and we observe a better performance compared to the standard use of ORCA. Finally, using realistic UAV traffic situations for delivery, we perform extensive simulations to study the potential occurrence and distribution of collisions, and to assess safety parameters for CDR.
With the ubiquity of smartphones, spatial crowdsourcing (SC) has emerged as a new paradigm that e... more With the ubiquity of smartphones, spatial crowdsourcing (SC) has emerged as a new paradigm that engages mobile users to perform tasks in the physical world. Thus, various SC techniques have been studied for performance optimization. However, little research has been done to understand workers' behavior in the real world. In this study, we designed and performed two real world SC campaigns utilizing our mobile app, called Genkii, which is a GPS-enabled app for users to report their affective state (e.g., happy, sad). We used Yahoo! Japan Crowdsourcing as the payment platform to reward users for reporting their affective states at different locations and times. We studied the relationship between incentives and participation by analyzing the impact of offering a fixed reward versus an increasing reward scheme. We observed that users tend to stay in a campaign longer when the provided incentives gradually increase over time. We also found that the degree of mobility is correlated with the reported information. For example, users who travel more are observed to be happier than the ones who travel less. Furthermore, analyzing the spatiotempo-ral information of the reports reveals interesting mobility patterns that are unique to spatial crowdsourcing.
Unmanned aerial vehicles (UAVs) operate with large degrees of autonomy when executing tasks from ... more Unmanned aerial vehicles (UAVs) operate with large degrees of autonomy when executing tasks from a ground-based controller. In this work, we design an (immersive) interface for drone management. Our interface supports operators in mission execution of one or several (automated) UAVs within a fleet. This allows operators to assign tasks to UAVs, while safe operations are ensured through in-flight conflict detection and prevention. Our interface fulfills both functional (e.g., reliability) and non-functional requirements (e.g., perceived cognitive load during use). A key design challenge is the latency in information exchanges, which introduces information asymmetries between the humans and UAVs. We then validate the effectiveness of our interface design across several experiments. We find that our design reduces the perceived cognitive load and improves task performance. Altogether, this work has implications for designing interfaces in human-machine collaboration, so humans can effe...
Unmanned aerial vehicles (UAVs) are expected to provide a wide range of services, whereby UAV fle... more Unmanned aerial vehicles (UAVs) are expected to provide a wide range of services, whereby UAV fleets will be managed by several independent service providers in shared low-altitude airspace. One important element, or redundancy, for safe and efficient UAV operation is pre-flight Conflict Detection and Resolution (CDR) methods that generate conflict-free paths for UAVs before the actual flight. Multi-Agent Path Finding (MAPF) has already been successfully applied to comparable problems with ground robots. However, most MAPF methods were tested with simplifying assumptions which do not reflect important characteristics of many real-world domains, such as delivery by UAVs where heterogeneous agents need to be considered, and new requests for flight operations are received continuously. In this paper, we extend CBS and ECBS to efficiently incorporate heterogeneous agents with computational geometry and we reduce the search space with spatio-temporal pruning. Moreover, our work introduce...
In future UAV-based services, UAV fleets will be managed by independent service providers in shar... more In future UAV-based services, UAV fleets will be managed by independent service providers in shared low-altitude airspace. Therefore, Conflict Detection and Resolution (CDR) methods that solve conflicts, i.e. possible collisions, between UAVs of all service providers are a key element of the Unmanned Aircraft System Traffic Management (UTM) system. We present a top-to-bottom algorithmic system with an extension to UAV operations of ORCA, a state-of-the-art algorithm in robotics. Then, using extreme-conflict situations, we empirically determine optimal parameter values for our adapted ORCA, and we observe a better performance compared to the standard use of ORCA. Finally, using realistic UAV traffic situations for delivery, we perform extensive simulations to study the potential occurrence and distribution of collisions, and to assess safety parameters for CDR.
With the ubiquity of smartphones, spatial crowdsourcing (SC) has emerged as a new paradigm that e... more With the ubiquity of smartphones, spatial crowdsourcing (SC) has emerged as a new paradigm that engages mobile users to perform tasks in the physical world. Thus, various SC techniques have been studied for performance optimization. However, little research has been done to understand workers' behavior in the real world. In this study, we designed and performed two real world SC campaigns utilizing our mobile app, called Genkii, which is a GPS-enabled app for users to report their affective state (e.g., happy, sad). We used Yahoo! Japan Crowdsourcing as the payment platform to reward users for reporting their affective states at different locations and times. We studied the relationship between incentives and participation by analyzing the impact of offering a fixed reward versus an increasing reward scheme. We observed that users tend to stay in a campaign longer when the provided incentives gradually increase over time. We also found that the degree of mobility is correlated with the reported information. For example, users who travel more are observed to be happier than the ones who travel less. Furthermore, analyzing the spatiotempo-ral information of the reports reveals interesting mobility patterns that are unique to spatial crowdsourcing.
Uploads