An overview of robotics and autonomous systems for harsh environments

Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

Standardized field testing of assistant robots in a Mars-like environment

Controlled testing on standard tasks and within standard environments can provide meaningful performance comparisons between robots of heterogeneous design. But because they must perform practical tasks in unstructured, and therefore non-standard, environments, the benefits of this approach have barely begun to accrue for field robots. This work describes a desert trial of six student prototypes of astronaut-support robots using a set of standardized engineering tests developed by the US National Institute of Standards and Technology (NIST), along with three operational tests in natural Mars-like terrain. The results suggest that standards developed for emergency response robots are also applicable to the astronaut support domain, yielding useful insights into the differences in capabilities between robots and real design improvements. The exercise shows the value of combining repeatable engineering tests with task-specific application-testing in the field

Adaptive and intelligent navigation of autonomous planetary rovers - A survey

The application of robotics and autonomous systems in space has increased dramatically. The ongoing Mars rover mission involving the Curiosity rover, along with the success of its predecessors, is a key milestone that showcases the existing capabilities of robotic technology. Nevertheless, there has still been a heavy reliance on human tele-operators to drive these systems. Reducing the reliance on human experts for navigational tasks on Mars remains a major challenge due to the harsh and complex nature of the Martian terrains. The development of a truly autonomous rover system with the capability to be effectively navigated in such environments requires intelligent and adaptive methods fitting for a system with limited resources. This paper surveys a representative selection of work applicable to autonomous planetary rover navigation, discussing some ongoing challenges and promising future research directions from the perspectives of the authors

Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges

Human-swarm interaction (HSI) involves a number of human factors impacting human behaviour throughout the interaction. As the technologies used within HSI advance, it is more tempting to increase the level of swarm autonomy within the interaction to reduce the workload on humans. Yet, the prospective negative effects of high levels of autonomy on human situational awareness can hinder this process. Flexible autonomy aims at trading-off these effects by changing the level of autonomy within the interaction when required; with mixed-initiatives combining human preferences and automation's recommendations to select an appropriate level of autonomy at a certain point of time. However, the effective implementation of mixed-initiative systems raises fundamental questions on how to combine human preferences and automation recommendations, how to realise the selected level of autonomy, and what the future impacts on the cognitive states of a human are. We explore open challenges that hamper the process of developing effective flexible autonomy. We then highlight the potential benefits of using system modelling techniques in HSI by illustrating how they provide HSI designers with an opportunity to evaluate different strategies for assessing the state of the mission and for adapting the level of autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling Conference, Canberra, Australi

Engineering News, Fall 2019

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