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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…

Semiautonomous rover scaling is examined for exploration throughout the solar system. Communications to a relay orbiter is a major constraint, due to power requirements and decreasing antenna gain at small sizes. Also, analysis time scales…

In flood disaster rescue scenarios, partially submerged buildings prevent aerial robots from accessing lower levels, limiting mission effectiveness. To address this challenge, this paper presents Wukong-Omni, a novel multimode robot capable…

Brain-computer interfaces (BCIs) provide a hands-free control modality for mobile robotics, yet decoding user intent during real-world navigation remains challenging. This work presents a brain-robot control framework for offline decoding…

The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2022 IEEE International Conference on Robotics and Automation (ICRA 2022) in Philadelphia, PA. The aim of the challenge was to evaluate state-of-the-art autonomous…

This paper shows and evaluates a novel approach to integrate a non-invasive Brain-Computer Interface (BCI) with the Robot Operating System (ROS) to mentally drive a telepresence robot. Controlling a mobile device by using human brain…

This paper introduces a novel Monte Carlo (MC) method to simulate the evolution of the low-earth orbit environment, enhancing the MIT Orbital Capacity Analysis Tool (MOCAT). In recent decades, numerous space environment models have been…

Terraforming Mars is an age old science fiction concept now worth revisiting through the lens of modern science and technology. This document serves as a summary of contemporary ideas about Mars terraforming, prepared for attendees of the…

In this paper, emerging deep learning techniques are leveraged to deal with Mars visual navigation problem. Specifically, to achieve precise landing and autonomous navigation, a novel deep neural network architecture with double branches…

The race for the most efficient, accurate, and universal algorithm in scientific computing drives innovation. At the same time, this healthy competition is only beneficial if the research output is actually comparable to prior results.…

In the emerging space economy, autonomous robotic missions with specialized goals such as mapping and mining are gaining traction, with agencies and enterprises increasingly investing resources. Multirobot systems (MRS) research has…

In robotic planetary surface exploration, strategic mobility planning is an important task that involves finding candidate long-distance routes on orbital maps and identifying segments with uncertain traversability. Then, expert human…

Precise perception of articulated objects is vital for empowering service robots. Recent studies mainly focus on point cloud, a single-modal approach, often neglecting vital texture and lighting details and assuming ideal conditions like…

Ensuring safety is crucial to promote the application of robot manipulators in open workspaces. Factors such as sensor errors or unpredictable collisions make the environment full of uncertainties. In this work, we investigate these…

Autonomous robots consistently encounter unforeseen dangerous situations during exploration missions. The characteristic rimless wheels in the AsguardIV rover allow it to overcome challenging terrains. However, steep slopes or difficult…

The DARPA Subterranean Challenge is leading the development of robots capable of mapping underground mines and tunnels up to 8km in length and identify objects and people. Developing these autonomous abilities paves the way for future…

Modular Aerial Robotic Systems (MARS) consist of multiple drone units assembled into a single, integrated rigid flying platform. With inherent redundancy, MARS can self-reconfigure into different configurations to mitigate rotor or unit…

Mixed Reality (MR) interfaces have been extensively explored for controlling mobile robots, but there is limited research on their application to managing teams of robots. This paper presents HORUS: Holistic Operational Reality for Unified…

Reinforcement learning (RL) is a promising field to enhance robotic autonomy and decision making capabilities for space robotics, something which is challenging with traditional techniques due to stochasticity and uncertainty within the…

The goal of RoboCup is to make research in the area of robotics measurable over time, and grow a community that works together to solve increasingly difficult challenges over the years. The most ambitious of these challenges it to be able…