Exponentially-declining launch costs have led to an explosion of inexpensive satellites launched to space, often equipped with off-the-shelf chips. These chips, however, lack hardware radiation protection, leaving them vulnerable to space radiation. We thus design Radshield, a software system protecting against the two most ubiquitous and costly radiation fault scenarios: (a) radiation-induced short-circuits that lead to permanent hardware failure; and (b) radiation-induced transient charges that result in single-bit silent data corruption (SDC). Radshield counters these failure scenarios with two components. First, it uses a short-circuit detector that can detect tiny increases in the device's current draw by estimating the normal current draw when resource utilization is low. Second, it duplicates the execution of spacecraft workloads in a CPU and memory-efficient manner, and catches SDCs even when they affect the CPU's pipeline or cache. In our experiments, we show Radshield is very effective at preventing both errors, and is 1.4-35.5× more power-efficient than the state-of-the-art protection mechanisms in detecting SDC. Radshield is deployed on missions in low-earth orbit and in deep space.

To achieve longer driving distances, planetary robotics missions require accurate localization to counteract position uncertainty. Freedom and precision in driving allows scientists to reach and study sites of interest. Typically, rover global localization has been performed manually by humans, which is accurate but time-consuming as data is relayed between planets. This paper describes a global localization algorithm that is run onboard the Perseverance Mars rover. Our approach matches rover images to orbital maps using a modified census transform to achieve sub-meter accurate, near-human localization performance on a real dataset of 264 Mars rover panoramas. The proposed solution has also been successfully executed on the Perseverance Mars Rover, demonstrating the practicality of our approach.

Due to their low cost and the need to run computationally-intensive algorithms locally, satellites and spacecraft are increasingly employing off-the-shelf computing hardware. However, hardware in space is exposed to significantly higher amounts of radiation than on Earth, potentially destroying the hardware or causing it to output incorrect results. We envision that solely using software fault tolerance techniques, commodity hardware operating in space can achieve fault tolerance equivalent or close to expensive and slow radiation-hardened hardware. To achieve this goal, we need to address the two main radiation fault scenarios: hardware overheating and silent data corruption. We provide preliminary data on the effects of these errors, and introduce a set of techniques to address them. Enabling the full use of commodity hardware in space holds the promise of improving the compute capabilities and cost effectiveness of low-earth orbit satellites by orders of magnitude.

The Atacama Desert of northern Chile may be the most lifeless place on Earth, yet where the desert meets the Pacific coastal range desiccation-tolerant micro-organisms are known to exist. The gradient of biodiversity and habitats in the Atacama’s subregions remain unexplored and are the focus of the Life in the Atacama project. To conduct this investigation, long traverses must be made across the desert with instruments for geologic and biologic measurements. In this paper we motivate the Life in the Atacama project from both astrobiologic and robotic perspectives. We focus on some of the research challenges we are facing to enable endurance navigation, resource cognizance, and long-term survivability. We conducted our first scientific investigation and technical experiments in Chile with the mobile robot Hyperion. We describe the experiments and the results of our analysis. These results give us insight into the design of an effective robotic astrobiologist and into the methods by which we will conduct scientific investigation in the next field season.

We propose a new particle filter that incorporates a model of costs when generating particles. The approach is motivated by the observation that the costs of accidentally not tracking hypotheses might be significant in some areas of state space, and next to irrelevant in others. By incorporat- ing a cost model into particle filtering, states that are more critical to the system performance are more likely to be tracked. Automatic calculation of the cost model is implemented using an MDP value function calcula- tion that estimates the value of tracking a particular state. Experiments in two mobile robot domains illustrate the appropriateness of the approach.

Autonomous planetary rovers operating in vast unknown environments must operate efficiently because of size, power and computing limitations. Recently, we have developed a rover capable of efficient obstacle avoidance and path planning. The rover uses binocular stereo vision to sense potentially cluttered outdoor environments. Navigation is performed by a combination of several modules that each "vote" for the next best action for the robot to execute. The key distinction of our system is that it produces globally intelligent behavior with a small computational resource - all processing and decision making are done on a single processor. These algorithms have been tested on our outdoor prototype rover, Bullwinkle, and have recently driven the rover 100 m at a speed of 15 cm/sec. In this paper we report on the extension on the systems that we have previously developed that were necessary to achieve autonomous navigation in this domain.