The simulations team is responsible for simulating the robot arm under different conditions and in different environments. So far, our team has learned the basics of ROS and created a URDF for the arm. Current semester goals are to create a launch file for our arm in Gazebo.

The Structures team is responsible for the design, analysis, and manufacturing of the mechanical subsystems within our robotic platforms. This includes conducting research and development to produce components capable of withstanding the extreme conditions associated with spaceflight. Structures works in close collaboration with the Electronics team to integrate hardware and develop the electromechanical functions required for autonomous operation.

The Structures team previously developed a 3-degree-of-freedom (DOF) robotic arm as an introductory project to establish core competencies in robotic arm design and fabrication. Currently, the team is advancing the design of a 4 DOF arm, optimized to operate within the dimensional constraints of a standard space station payload locker. This project focuses on developing systems capable of surviving launch loads while maintaining functionality in microgravity. The arm features compact series elastic actuators to enable force feedback and precise motion control, and the end effector is designed with a modular tool-changer interface, allowing for adaptable interactions with various end-effectors and payloads.

The Electronics subteam of Astrobotics is responsible for designing, testing, and integrating the electrical systems that power and control our robotic inchworm arm. Our primary focus is on developing reliable electronics for space applications, starting with a subscale arm to test movement in zero-gravity environments. We provide training in basic and space-grade electronics, PCB design using software like Altium, EAGLE, and Fusion, and host hands-on soldering labs for our members. Through our onboarding process, new members gain the foundational skills needed to contribute to our cutting-edge research in space assembly and manufacturing.

The Machine Learning subteam is primarily focused on developing crucial software for operating the robot arm, ensuring that it is able to complete all necessary tasks. From developing computer vision models to programming robot control algorithms, the Machine Learning team focuses on providing perception and robust movement to our robot arm.

The Machine Learning subteam is tasked with two main goals this semester: to get object detection working for our arm and to make progress on arm movement simulation. For object detection, we have finished our set-up for performing depth perception and object detection with a monocular camera. We are currently working on improving our model and implementing it into more advanced sensors/cameras that meet the requirements for space. This set-up leverages technologies such as AprilTags, Python’s OpenCV, and more. For arm kinematics, the team has currently been learning robot software tools such as ROS2, MoveIT, and Gazebo, and we plan to experiment with URDF files before the end of the semester.

The Astrobotics Business Team fosters real-world relationships with competitive companies, ensuring strong industry connections and collaboration. Additionally, the team plays a crucial role in maintaining clear and effective communication with the community, promoting awareness, engagement, and support for our initiatives.