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Abstract-We present the adaptation of an optimal terrain coverage algorithm for the aerial robotics domain. The general strategy involves computing a trajectory through a known environment with obstacles that ensures complete coverage of the terrain while minimizing path repetition. We introduce a system that applies and extends this generic algorithm to achieve automated terrain coverage using an aerial vehicle. Extensive experimental results in simulation validate the presented system, along with data from over 100 kilometers of successful coverage flights using a fixed-wing aircraft.

Aims To integrate the overall effect of e‐health based self‐management on cancer‐related fatigue (CRF), self‐efficacy, and quality of life (QOL) among adult cancer patients. Design A systematic review and meta‐analysis of randomized controlled trials. Data sources We researched PubMed, Cumulative Index Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Web of Science and Embase up to 14 July 2019. Review Methods We conducted the review with the Cochrane Handbook (version 5.1.0) and measured the quality of evidence with the Grading of Recommendations Assessment, Development and Evaluation criteria. Results Literature searching identified 15 trials with a total of 2,337 participants. Integrated results analysis of e‐health based self‐management demonstrated a statistically significant but small effect on CRF and self‐efficacy, but no statistically significant improvement on the QOL. Meanwhile, subgroup analysis indicated that e‐health based self‐management had a larger effect on fatigue compared with usual care/waiting list control. Conclusion E‐health based self‐management is effective for CRF and self‐efficacy, but not the QOL. More high‐quality randomized control trials are warranted to confirm these conclusions. Impact Results showed e‐health could improve fatigue and self‐efficacy but not the QOL. Health providers could take into the various factors of e‐health interventions when providing telehealth service. Other researchers might be inspired by the current review before they begin a study about e‐health.

Abstract-In this paper we describe a heterogeneous multirobot system for assisting scientists in environmental monitoring tasks, such as the inspection of marine ecosystems. This team of robots is comprised of a fixed-wing aerial vehicle, an autonomous airboat, and an agile legged underwater robot. These robots interact with off-site scientists and operate in a hierarchical structure to autonomously collect visual footage of interesting underwater regions, from multiple scales and mediums. We discuss organizational and scheduling complexities associated with multi-robot experiments in a field robotics setting. We also present results from our field trials, where we demonstrated the use of this heterogeneous robot team to achieve multi-domain monitoring of coral reefs, based on realtime interaction with a remotely-located marine biologist.

Abstract-We describe an interaction paradigm for controlling a robot using hand gestures. In particular, we are interested in the control of an underwater robot by an onsite human operator. Under this context, vision-based control is very attractive, and we propose a robot control and programming mechanism based on visual symbols. A human operator presents engineered visual targets to the robotic system, which recognizes and interprets them. This paper describes the approach and proposes a specific gesture language called "RoboChat". RoboChat allows an operator to control a robot and even express complex programming concepts, using a sequence of visually presented symbols, encoded into fiducial markers. We evaluate the efficiency and robustness of this symbolic communication scheme by comparing it to traditional gesture-based interaction involving a remote human operator.