This work presents an innovative solution for robotic odometry, path planning and exploration in wild unknown environments, focusing on digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated objectives, integrating multi-path planning and evaluation, with emphasis on full coverage of unknown maps based on feasible boundaries of interest. The evaluation carried out on a robotic platform with a lightweight 3D LiDAR sensor model, assesses the consistency and efficiency in exploring completely unknown subterranean-like areas. The algorithm allows for dynamic changes to the desired target and behaviour. At the same time, the paper details the design of AREX, highlighting its robust localisation, mapping and efficient exploration target selection capabilities, with a focus on continuity in exploration direction for increased efficiency and reduced odometry errors. The real-time, high-precision environmental perception module is identified as critical for accurate obstacle avoidance and exploration boundary identification.

Mapping and exploration of a Martian terrain with an aerial vehicle has become an emerging research direction, since the successful flight demonstration of the Mars helicopter Ingenuity. Although the autonomy and navigation capability of the state of the art Mars helicopter has proven to be efficient in an open environment, the next area of interest for exploration on Mars are caves or ancient lava tube like environments, especially towards the never-ending search of life on other planets. This article presents an autonomous exploration mission based on a modified frontier approach along with a risk aware planning and integrated collision avoidance scheme with a special focus on energy aspects of a custom designed Mars Coaxial Quadrotor (MCQ) in a Martian simulated lava tube. One of the biggest novelties of the article stems from addressing the exploration capability, while rapidly exploring in local areas and intelligently global re-positioning of the MCQ when reaching dead ends in order to to efficiently use the battery based consumed energy, while increasing the volume of the exploration. The proposed novel algorithm for the Martian exploration is able to select the next way point of interest, such that the MCQ keeps its heading towards the local exploration direction where it will find maximum information about the surroundings. The proposed three layer cost based global re-position point selection assists in rapidly redirecting the MCQ to previously partially seen areas that could lead to more unexplored part of the lava tube. The Martian fully simulated mission presented in this article takes into consideration the fidelity of physics of Mars condition in terms of thin atmosphere, low surface pressure and low gravity of the planet, while proves the efficiency of the proposed scheme in exploring an area that is particularly challenging due to the subterranean-like environment. The proposed exploration-planning framework is also validated in simulation by comparing it against the graph based exploration planner. Intensive simulations with true Mars conditions are carried out in order to validate and benchmark our approach in a utmost realistic Mars lava tube exploration scenario using a Mars Coaxial Quadrotor.

Exploration and mapping of unknown environments is a fundamental task in applications for autonomous robots. In this article, we present a complete framework for deploying MAVs in autonomous exploration missions in unknown subterranean areas. The main motive of exploration algorithms is to depict the next best frontier for the robot such that new ground can be covered in a fast, safe yet efficient manner. The proposed framework uses a novel frontier selection method that also contributes to the safe navigation of autonomous robots in obstructed areas such as subterranean caves, mines, and urban areas. The framework presented in this work bifurcates the exploration problem in local and global exploration. The proposed exploration framework is also adaptable according to computational resources available onboard the robot which means the trade-off between the speed of exploration and the quality of the map can be made. Such capability allows the proposed framework to be deployed in a subterranean exploration, mapping as well as in fast search and rescue scenarios. The overall system is considered a low-complexity and baseline solution for navigation and object localization in tunnel-like environments. The performance of the proposed framework is evaluated in detailed simulation studies with comparisons made against a high-level exploration-planning framework developed for the DARPA Sub-T challenge as it will be presented in this article.

It looks like mankind won't be going back to the moon … on schedule, at least. According to a recent report by the National Aeronautics and Space Administration's inspector general, astronaut suits have been delayed by two years due to an array of technical, funding and COVID-related challenges. But, the unavoidable conclusion, "a lunar landing in late 2024 as NASA currently plans is not feasible," is hardly surprising given NASA's string of failures in trying to take humanity back to the lunar surface. The failures also speak to a larger strategic mistake that places inordinate importance on planting flags on alien worlds despite the practical and scientific disadvantages of that approach. Humanity can venture to infinity and beyond while avoiding the black hole of wasteful spending.

The use of AI in space exploration is increasing at an unprecedented pace, with the market being valued at a staggering $2 billion and still growing. Richard Branson, founder of Virgin Galactic successfully soared to space on Sunday. Ex-Amazon boss, Jeff Bezos of Blue Origin is the next billionaire to travel to space this month. While these are potential space tourism initiatives, the space race began ever since humans found that there exists a place beyond earth. Starting with the launch of Sputnik in 1957, and the first man landing on the moon a decade later, the race to space was always on with nations trying their hands on exploring this exciting frontier.

BREVARD COUNTY, Fla. – Elton John might have said it best in his iconic song "Rocket Man" – "Mars ain't the kind of place to raise your kids." More than 50 years after we sent humans to the moon – the closest celestial body to Earth – the plan is still to head to Mars, something many astronauts who have flown in space thought we would have already accomplished. "I just assumed by the time I got to be old enough to go into the space program, you know we'd be living on Mars or I'd be working on Mars just as a scientist," Mae Jemison, the first African American woman in space, told university students at the Kennedy Space Center Visitor Complex in December 2019. But despite the fact humankind has been unable to send anyone to another place in the universe besides the moon, there are still many with the hopes and expectation that we will become a multi-planetary species in the near future, starting with our red next-door neighbor. Billionaire entrepreneurs like Elon Musk and aspiring young astronauts like Alyssa Carson, a sophomore studying astrobiology at Florida Tech, hope to one day live on Mars. "Eventually the sun will run out of fuel to burn … and conditions on Earth are going to be very different from our normal regular life now," Carson told Florida Today, part of the USA TODAY Network.