Astervey

A few days ago, we posted about the importance of low thrust propulsion in interplanetary mission design. Today, NASA announced SR-1 Freedom, a nuclear powered interplanetary spacecraft targeting a Mars mission by 2028. The spacecraft uses a 20+ kilowatt fission reactor powering xenon ion thrusters. Low thrust ion propulsion delivers ISPs of thousands of seconds, far exceeding anything chemical propulsion can offer. The tradeoff is acceleration time, but for long deep space missions, continuous low thrust beats a single impulsive burn in terms of fuel mass and mission flexibility. This is exactly the design space Astervey's trajectory tool was built for. Modeling optimal low thrust control across an interplanetary arc is a genuinely hard problem, and having that capability in house becomes increasingly relevant as nuclear electric propulsion moves from theory to actual flight heritage. The real significance of SR-1 goes beyond Mars. It sets regulatory precedent for nuclear hardware in space, activates the industrial base, and opens the door to high power missions beyond Jupiter where solar arrays simply stop being viable. #NASA #Mars #NuclearPropulsion

NASA has just canceled the Lunar Gateway, redirecting resources toward a permanent lunar surface base by 2036. The urgency is clear as China is targeting its own Moon landing by 2030, and NASA is racing to land astronauts as early as 2028. A surface base is a stronger, more permanent foothold on the Moon, and the strategic focus makes sense. The concern is what gets left behind. Key hardware was already built and delivered by international partners like ESA and JAXA, and NASA needs a plan to repurpose it. What are your thoughts? Is this the right trade-off, or does abandoning Gateway do more damage than good? #NASA #Lunar #Gateway #MoonBase #SpaceNews

The Mars Climate Orbiter is a well-known reminder of how small errors can have mission-ending consequences. A unit mismatch between teams led to the spacecraft entering the Martian atmosphere at the wrong trajectory, ultimately resulting in the loss of the $327 million dollar vehicle. Beyond the specific cause, the failure highlights a broader challenge in deep-space missions: limited onboard autonomy and too much reliance on ground-based corrections. Incorporating optical autonomous navigation could have added a valuable layer of redundancy. By enabling a spacecraft to independently determine its relative pose using onboard imaging, deviations can be detected and corrected in real time, reducing dependence on external inputs and minimizing the risk of compounding errors. While this technology was not feasible for the Mars Climate Orbiter, it is today. Astervey is building toward this future with self-piloting software designed to bring greater autonomy to spacecraft navigation. By combining advanced guidance, navigation, and control with onboard decision-making, missions can become more resilient, adaptable, and ultimately more successful. We’re curious to hear from you, where else could onboard autonomy make the biggest difference? #spacecraft #autonomous #GNC #spaceExploration

You cannot discuss interplanetary travel without considering solar sails. By using solar radiation pressure, solar sails provide propulsion without needing to carry fuel onboard. Solar sails appear in mission concepts between the inner planets, high-velocity rendezvous and capture scenarios, and within the Earth-Moon system. While the technology continues to develop, a major challenge remains: planning control strategies for optimal trajectories. Astervey has built a tool that designs the precise control inputs required for optimal low-thrust trajectory design. This capability makes mission planning and concept development for low-thrust missions more accessible. If you’re interested in learning more about this capability, check us out! #aerospace #astrodynamics #lowthrust #trajectoryoptimization

For interplanetary mission planning, it is important to consider low-thrust propulsion. Systems such as solar sails and ion thrusters can enable missions with larger payloads, easier orbit insertion, and greater mission flexibility. However, determining #optimal #orbit #trajectories under continuous low thrust is a unique and challenging problem. To support our future #interplanetary missions and our #asteroid selection tool, DAKOTA, Astervey has developed a computationally efficient software tool to address this challenge. The tool currently models near-circular orbit insertions across a range of thrust levels.

NASA lost contact with its low-cost Lunar Trailblazer probe just one day after launch. The issue? The spacecraft’s solar panels were oriented 180 degrees away from the Sun (not ideal). The root cause was a simple but critical configuration error; the gimbal axes were defined incorrectly, effectively flipping the direction of motion. This mistake, undetected during testing, ended the mission before it could begin and resulted in a $72 million loss for #NASA. It is a devastating outcome for the #Trailblazer team and reinforces the long-standing concern in spaceflight that lower-cost missions often carry higher risk. Compressed timelines and tighter budgets can limit testing and fault management. However, advances in AI are changing this equation. Astervey’s self-piloting satellite software builds on traditional fault detection systems by integrating agentic AI reasoning to diagnose root causes and autonomously implement corrective actions. In time-critical scenarios, this capability can mean the difference between mission recovery and mission failure. Even in cases where ground contact is temporarily lost, the system can operate independently to resolve issues and restore communications. Astervey essentially places an expert-level decision-making astronaut onboard every satellite, protecting both scientific objectives and program budgets. The loss of Lunar Trailblazer is a sobering reminder of how fragile space missions can be. But it also underscores the need for smarter onboard systems that can detect, diagnose, and resolve faults in real time, adding resiliency to our most valuable assets.

Space is cold, GPUs need cooling, so let’s put AI data centers in orbit. Right? The physics is more complicated. Although deep space has a background temperature near 3 Kelvin, a spacecraft cannot cool itself simply by being surrounded by “cold.” In orbit there is no air, so there is no convection or conduction to the environment. The only way to reject heat is through thermal radiation. Radiative cooling works, but it requires large radiator surfaces, heat transport systems, and careful thermal control. This adds mass, complexity, and cost. Another commonly cited advantage of AI space data centers is solar power efficiency. It's true; satellites are exposed to intense solar radiation, as there are no clouds or atmosphere to interfere. This directly contradicts the “space is cold” logic. Sunlight is absorbed and adds to the waste heat generated by GPUs. In steady state, all of that energy must be radiated away. If it is not, the system overheats. Space-based AI data centers are technically feasible, and yes, they do generate more electricity from solar power. However, they are very bad at cooling. Combined with the cost of procurement, launch, and maintenance, it may make economical sense to stay on Earth. However, there is still a place for AI in space. At Astervey, we focus on embedding AI directly onboard satellites to enable real-time decision-making, autonomous maneuvering, and anomaly detection. Whether it is an Earth-observing satellite redirecting its camera away from cloud cover or a spacecraft avoiding a potential debris collision, AI in space enables satellites to operate independently and accomplish their missions more effectively. #AI #SpaceDataCenters #SpaceTech #EdgeComputing

Past asteroid mining ventures show how capital-intensive and risk-sensitive deep space missions can be. The bottleneck is mission uncertainty and long capital timelines. Astervey builds #autonomy and #AIML software to reduce costs and uncertainty, enabling rapidly-deployable and low-cost satellites. Our 5 levels of satellite automation are a roadmap towards fully autonomous navigation, fault detection and correction, and onboard decision-making. You can learn more about the 5 levels of satellite automation on our website. Alongside our mission towards full satellite autonomy, we'd like to share our work with the new Dynamic Asteroid Knowledge & Orbital Targeting Algorithm (DAKOTA). DAKOTA narrows the ~1.5M cataloged asteroids to a small set of viable targets by optimizing trajectory feasibility and solving for operational unknowns (e.g. mineral composition, rotation rate, size and shape). DAKOTA reduces the cost and risk of an asteroid exploration mission, making it a useful tool for mission designers. DAKOTA is currently in demo phase as we refine the architecture and validation pipeline. #asteroidMining #spaceExploration