SmallSatSim: A High-Fidelity Simulation and Training Toolkit for Microgravity Robotic Close Proximity Operations

Microgravity rendezvous and close proximity operations (RPO) is a growing area of interest for applications spanning in-space assembly and manufacturing (ISAM), orbital debris remediation, and small body exploration. Microgravity environments present unique challenges for robotic control and planning algorithms for new agile RPO mission scenarios like free-floating manipulation, planning under failure, and estimating high-fidelity dynamics of tumbling bodies. To facilitate the development and testing of novel RPO algorithms, we introduce SmallSatSim, a high-fidelity simulation toolkit that leverages the MuJoCo physics engine to accurately model small satellite RPO dynamics in local microgravity robotic free-flight settings, including under model disturbances and perturbations. The framework includes cutting edge out-of-the-box free-flyer control techniques. A GPU-accelerated pipeline using MuJoCo MJX and JAX is implemented for sampling- and learning-based simulation uses cases. SmallSatSim also supports configurable failure models, enabling the evaluation of safe control strategies under adversarial conditions. Visualization, logging, and GPU-enabled parallelization further enhance SmallSatSim's capability for RPO testing. We outline SmallSatSim's features and intended use cases, and demonstrate its use for robotic RPO planning and control. The open-sourced toolkit aims to accelerate research in autonomous, agile robotic small satellite operations.

Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing

Diffusion models hold great potential in robotics due to their ability to capture complex, high-dimensional data distributions. However, their lack of constraint-awareness limits their deployment in safety-critical applications. We propose Constraint-Aware Diffusion Guidance (CoDiG), a data-efficient and general-purpose framework that integrates barrier functions into the denoising process, guiding diffusion sampling toward constraint-satisfying outputs. CoDiG enables constraint satisfaction even with limited training data and generalizes across tasks. We evaluate our framework in the challenging setting of miniature autonomous racing, where real-time obstacle avoidance is essential. Real-world experiments show that CoDiG generates safe outputs efficiently under dynamic conditions, highlighting its potential for broader robotic applications. A demonstration video is available at https://youtu.be/KNYsTdtdxOU.

Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot

This paper presents an open-source miniature car-like robot with low-cost sensing and a pipeline for optimization-based system identification, state estimation, and control. The overall robotics platform comes at a cost of less than $700 and thus significantly simplifies the verification of advanced algorithms in a realistic setting. We present a modified bicycle model with Pacejka tire forces to model the dynamics of the considered all-wheel drive vehicle and to prevent singularities of the model at low velocities. Furthermore, we provide an optimization-based system identification approach and a moving horizon estimation (MHE) scheme. In extensive hardware experiments, we show that the presented system identification approach results in a model with high prediction accuracy, while the MHE results in accurate state estimates. Finally, the overall closed-loop system is shown to perform well even in the presence of sensor failure for limited time intervals. All hardware, firmware, and control and estimation software is released under a BSD 2-clause license to promote widespread adoption and collaboration within the community.

Chronos and CRS: Design of a miniature car-like robot and a software framework for single and multi-agent robotics and control

From both an educational and research point of view, experiments on hardware are a key aspect of robotics and control. In the last decade, many open-source hardware and software frameworks for wheeled robots have been presented, mainly in the form of unicycles and car-like robots, with the goal of making robotics accessible to a wider audience and to support control systems development. Unicycles are usually small and inexpensive, and therefore facilitate experiments in a larger fleet, but they are not suited for high-speed motion. Car-like robots are more agile, but they are usually larger and more expensive, thus requiring more resources in terms of space and money. In order to bridge this gap, we present Chronos, a new car-like 1/28th scale robot with customized open-source electronics, and CRS, an open-source software framework for control and robotics. The CRS software framework includes the implementation of various state-of-the-art algorithms for control, estimation, and multi-agent coordination. With this work, we aim to provide easier access to hardware and reduce the engineering time needed to start new educational and research projects.