Earth's gravity has fundamentally shaped human development by guiding the brain's integration of vestibular, visual, and proprioceptive inputs into an internal model of gravity: a dynamic neural representation enabling prediction and interpretation of gravitational forces. This work presents a dual computational framework to quantitatively model these adaptations. The first component is a lightweight Multi-Layer Perceptron (MLP) that predicts g-load-dependent changes in key electroencephalographic (EEG) frequency bands, representing the brain's cortical state. The second component utilizes a suite of independent Gaussian Processes (GPs) to model the body's broader physiological state, including Heart Rate Variability (HRV), Electrodermal Activity (EDA), and motor behavior. Both models were trained on data derived from a comprehensive review of parabolic flight literature, using published findings as anchor points to construct robust, continuous functions. To complement this quantitative analysis, we simulated subjective human experience under different gravitational loads, ranging from microgravity (0g) and partial gravity (Moon 0.17g, Mars 0.38g) to hypergravity associated with spacecraft launch and re-entry (1.8g), using a large language model (Claude 3.5 Sonnet). The model was prompted with physiological parameters to generate introspective narratives of alertness and self-awareness, which closely aligned with the quantitative findings from both the EEG and physiological models. This combined framework integrates quantitative physiological modeling with generative cognitive simulation, offering a novel approach to understanding and predicting human performance in altered gravity

Space poses significant challenges for human physiology, leading to physiological adaptations in response to an environment vastly different from Earth. While these adaptations can be beneficial, they may not fully counteract the adverse impact of space-related stressors. A comprehensive understanding of these physiological adaptations is needed to devise effective countermeasures to support human life in space. This review focuses on the impact of the environment in space on the musculoskeletal system. It highlights the complex interplay between bone and muscle adaptation, the underlying physiological mechanisms, and their implications on astronaut health. Furthermore, the review delves into the deployed and current advances in countermeasures and proposes, as a perspective for future developments, wearable sensing and robotic technologies, such as exoskeletons, as a fitting alternative.

We present SpaceAgents-1, a system for learning human and multi-robot collaboration (HMRC) strategies under microgravity conditions. Future space exploration requires humans to work together with robots. However, acquiring proficient robot skills and adept collaboration under microgravity conditions poses significant challenges within ground laboratories. To address this issue, we develop a microgravity simulation environment and present three typical configurations of intra-cabin robots. We propose a hierarchical heterogeneous multi-agent collaboration architecture: guided by foundation models, a Decision-Making Agent serves as a task planner for human-robot collaboration, while individual Skill-Expert Agents manage the embodied control of robots. This mechanism empowers the SpaceAgents-1 system to execute a range of intricate long-horizon HMRC tasks.

Mobility on asteroids by multi-limbed climbing robots is expected to achieve our exploration goals in such challenging environments. We propose a mobility strategy to improve the locomotion safety of climbing robots in such harsh environments that picture extremely low gravity and highly uneven terrain. Our method plans the gait by decoupling the base and limbs' movements and adjusting the main body pose to avoid ground collisions. The proposed approach includes a motion planning that reduces the reactions generated by the robot's movement by optimizing the swinging trajectory and distributing the momentum. Lower motion reactions decrease the pulling forces on the grippers, avoiding the slippage and flotation of the robot. Dynamic simulations and experiments demonstrate that the proposed method could improve the robot's mobility on the surface of asteroids.

Does gravity affect decision-making? This question comes into sharp focus as plans for interplanetary human space missions solidify. In the framework of Bayesian brain theories, gravity encapsulates a strong prior, anchoring agents to a reference frame via the vestibular system, informing their decisions and possibly their integration of uncertainty. What happens when such a strong prior is altered? We address this question using a self-motion estimation task in a space analog environment under conditions of altered gravity. Two participants were cast as remote drone operators orbiting Mars in a virtual reality environment on board a parabolic flight, where both hyper- and microgravity conditions were induced. From a first-person perspective, participants viewed a drone exiting a cave and had to first predict a collision and then provide a confidence estimate of their response. We evoked uncertainty in the task by manipulating the motion's trajectory angle. Post-decision subjective confidence reports were negatively predicted by stimulus uncertainty, as expected. Uncertainty alone did not impact overt behavioral responses (performance, choice) differentially across gravity conditions. However microgravity predicted higher subjective confidence, especially in interaction with stimulus uncertainty. These results suggest that variables relating to uncertainty affect decision-making distinctly in microgravity, highlighting the possible need for automatized, compensatory mechanisms when considering human factors in space research.

Robotic mobility in microgravity is necessary to expand human utilization and exploration of outer space. Bio-inspired multi-legged robots are a possible solution for safe and precise locomotion. However, a dynamic motion of a robot in microgravity can lead to failures due to gripper detachment caused by excessive motion reactions. We propose a novel Reaction-Aware Motion Planning (RAMP) to improve locomotion safety in microgravity, decreasing the risk of losing contact with the terrain surface by reducing the robot's momentum change. RAMP minimizes the swing momentum with a Low-Reaction Swing Trajectory (LRST) while distributing this momentum to the whole body, ensuring zero velocity for the supporting grippers and minimizing motion reactions. We verify the proposed approach with dynamic simulations indicating the capability of RAMP to generate a safe motion without detachment of the supporting grippers, resulting in the robot reaching its specified location. We further validate RAMP in experiments with an air-floating system, demonstrating a significant reduction in reaction forces and improved mobility in microgravity.

A tiny robot known as MIRA will be blasting off to the International Space Station (ISS) in 2024 to perform simulated surgical procedures in microgravity. MIRA, or "Miniaturized in vivo Robotic Assistant," will fly to the International Space Station thanks to a $100,000 award to the University of Nebraska-Lincoln through the U.S. Department of Energy's Established Program to Stimulate Competitive Research (EPSCoR). The technology involved could in the future provide a solution to medical emergencies requiring surgical intervention while astronauts are far from home, such as on a mission to Mars. First though, the 2024 test mission will see MIRA operate within an experimental locker the size of a microwave aboard ISS in low-Earth orbit. The aim will be to fine-tune the robot's operation in microgravity through autonomous tests including cutting stretched rubber bands and pushing metal rings along a wire, mimicking movements used in surgery.

While the idea of living on Mars may sound like the plot of the latest science fiction blockbuster, firms including NASA and SpaceX are seriously considering it as a possibility. Several challenges currently stand in our way, including building a self-sufficient spacecraft that can take crew safely, and finding a way to shield astronauts from dangerous solar and cosmic radiation - not to mention enabling them to live in microgravity on a planet with no atmosphere. This week, Lord Martin Rees, one of the country's leading astronomers, claimed that the obvious solution to some of these problems is making future explorers part-cyborg. Lord Rees told the Hay Festival: 'These intrepid explorers on Mars will be out of the clutches of the regulators and they will have every incentive to modify themselves because they are very badly adapted for Mars. 'They will use all these techniques to adapt themselves.

If faced with the choice of sending a swarm of full-sized, distinct robots to space, or a large crew of smaller robotic modules, you might want to enlist the latter. Modular robots, like those depicted in films such as "Big Hero 6," hold a special type of promise for their self-assembling and reconfiguring abilities. But for all of the ambitious desire for fast, reliable deployment in domains extending to space exploration, search and rescue, and shape-shifting, modular robots built to date are still a little clunky. They're typically built from a menagerie of large, expensive motors to facilitate movement, calling for a much-needed focus on more scalable architectures -- both up in quantity and down in size. Scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) called on electromagnetism -- electromagnetic fields generated by the movement of electric current -- to avoid the usual stuffing of bulky and expensive actuators into individual blocks.

Scientists from MIT's Computer Science and Artificial Intelligence Laboratory ( CSAIL) and the University of Calgary have developed a modular robot system that can morph into different shapes. ElectroVoxels don't have any motors or moving parts. Instead, they use electromagnets to shift around each other. Each edge of an ElectroVoxel cube is an electromagnetic ferrite core wrapped with copper wire. The length of each ElectroVoxel side is around 60 millimeters.