Mark R. Cutkosky

Hao Li, Long Yin Chung, Jack Goler et al.

Underwater robotic grasping is difficult due to degraded, highly variable imagery and the expense of collecting diverse underwater demonstrations. We introduce a system that (i) autonomously collects successful underwater grasp demonstrations via a self-supervised data collection pipeline and (ii) transfers grasp knowledge from on-land human demonstrations through a depth-based affordance representation that bridges the on-land-to-underwater domain gap and is robust to lighting and color shift. An affordance model trained on on-land handheld demonstrations is deployed underwater zero-shot via geometric alignment, and an affordance-conditioned diffusion policy is then trained on underwater demonstrations to generate control actions. In pool experiments, our approach improves grasping performance and robustness to background shifts, and enables generalization to objects seen only in on-land data, outperforming RGB-only baselines. Code, videos, and additional results are available at https://umi-under-water.github.io.

Stanley Wang, Velin Kojouharov, Long Yin Chung et al.

Commercial lunar activity is accelerating the need for reliable surface infrastructure and routine operations to keep it functioning. Maintenance tasks such as inspection, cleaning, dust mitigation, and minor repair are essential to preserve performance and extend system life. A specific application is the cleaning of lunar solar arrays. Solar arrays are expected to provide substantial fraction of lunar surface power and operate for months to years, supplying continuous energy to landers, habitats, and surface assets, making sustained output mission-critical. However, over time lunar dust accumulates on these large solar arrays, which can rapidly degrade panel output and reduce mission lifetime. We propose a small mobile robot equipped with a long-reach, lightweight deployable boom and interchangeable cleaning tool to perform gentle cleaning over meter-scale workspaces with minimal human involvement. Building on prior vision-guided long-reach manipulation, we add a compliant wrist with distal force sensing and a velocity-based admittance controller to regulate stable contact during surface cleaning. In preliminary benchtop experiments on a planar surface, the system maintained approximately 2 N normal force while executing a simple cleaning motion over boom lengths from 0.3 m to 1.0 m, with RMS force error of approximately 0.2 N after initial contact. These early results suggest that deployable long-reach manipulators are a promising architecture for robotic maintenance of lunar infrastructure such as solar arrays, radiators, and optical surfaces.

Hao Li, Chengyi Xing, Saad Khan et al. · stanford

Aquatic mammals, such as pinnipeds, utilize their whiskers to detect and discriminate objects and analyze water movements, inspiring the development of robotic whiskers for sensing contacts, surfaces, and water flows. We present the design and application of underwater whisker sensors based on Fiber Bragg Grating (FBG) technology. These passive whiskers are mounted along the robot$'$s exterior to sense its surroundings through light, non-intrusive contacts. For contact tracking, we employ a sim-to-real learning framework, which involves extensive data collection in simulation followed by a sim-to-real calibration process to transfer the model trained in simulation to the real world. Experiments with whiskers immersed in water indicate that our approach can track contact points with an accuracy of $<2$ mm, without requiring precise robot proprioception. We demonstrate that the approach also generalizes to unseen objects.

Stephanie Schneider, Andrew Bylard, Tony G. Chen et al.

Robots are widely deployed in space environments because of their versatility and robustness. However, adverse gravity conditions and challenging terrain geometry expose the limitations of traditional robot designs, which are often forced to sacrifice one of mobility or manipulation capabilities to attain the other. Prospective climbing operations in these environments reveals a need for small, compact robots capable of versatile mobility and manipulation. We propose a novel robotic concept called ReachBot that fills this need by combining two existing technologies: extendable booms and mobile manipulation. ReachBot leverages the reach and tensile strength of extendable booms to achieve an outsized reachable workspace and wrench capability. Through their lightweight, compactable structure, these booms also reduce mass and complexity compared to traditional rigid-link articulated-arm designs. Using these advantages, ReachBot excels in mobile manipulation missions in low gravity or that require climbing, particularly when anchor points are sparse. After introducing the ReachBot concept, we discuss modeling approaches and strategies for increasing stability and robustness. We then develop a 2D analytical model for ReachBot's dynamics inspired by grasp models for dexterous manipulators. Next, we introduce a waypoint-tracking controller for a planar ReachBot in microgravity. Our simulation results demonstrate the controller's robustness to disturbances and modeling error. Finally, we briefly discuss next steps that build on these initially promising results to realize the full potential of ReachBot.

Alexander M. Gruebele, Andrew C. Zerbe, Margaret M. Coad et al.

Due to their ability to move without sliding relative to their environment, soft growing robots are attractive for deploying distributed sensor networks in confined spaces. Sensing of the state of such robots would also add to their capabilities as human-safe, adaptable manipulators. However, incorporation of distributed sensors onto soft growing robots is challenging because it requires an interface between stiff and soft materials, and the sensor network needs to undergo significant strain. In this work, we present a method for adding sensors to soft growing robots that uses flexible printed circuit boards with self-contained units of microcontrollers and sensors encased in a laminate armor that protects them from unsafe curvatures. We demonstrate the ability of this system to relay directional temperature and humidity information in hard-to-access spaces. We also demonstrate and characterize a method for sensing the growing robot shape using inertial measurement units deployed along its length, and develop a mathematical model to predict its accuracy. This work advances the capabilities of soft growing robots, as well as the field of soft robot sensing.

A. Cauligi, T. G. Chen, S. A. Suresh et al.

Assistive free-flying robots are a promising platform for supporting and working alongside astronauts in carrying out tasks that require interaction with the environment. However, current free-flying robot platforms are limited by existing manipulation technologies in being able to grasp and manipulate surrounding objects. Instead, gecko-inspired adhesives offer many advantages for an alternate grasping and manipulation paradigm for use in assistive free-flyer applications. In this work, we present the design of a gecko-inspired adhesive gripper for performing perching and grasping maneuvers for the Astrobee robot, a free-flying robot currently operating on-board the International Space Station. We present software and hardware integration details for the gripper units that were launched to the International Space Station in 2019 for in-flight experiments with Astrobee. Finally, we present preliminary results for on-ground experiments conducted with the gripper and Astrobee on a free-floating spacecraft test bed.

Mine Sarac, Tae Myung Huh, Hojung Choi et al.

Our aim is to provide effective interaction with virtual objects, despite the lack of co-location of virtual and real-world contacts, while taking advantage of relatively large skin area and ease of mounting on the forearm. We performed two human participant studies to determine the effects of haptic feedback in the normal and shear directions during virtual manipulation using haptic devices worn near the wrist. In the first study, participants performed significantly better while discriminating stiffness values of virtual objects when the feedback consisted of normal displacements compared to shear displacements. Participants also commented that they could detect normal cues much easier than shear, which motivated us to perform a second study to find the point of subjective equality (PSE) between normal and shear stimuli. Our results show that shear stimuli require a larger actuator displacement but less force than normal stimuli to achieve perceptual equality for our haptic bracelets. We found that normal and shear stimuli cannot be equalized through skin displacement nor the interaction forces across all users. Rather, a calibration method is needed to find the point of equality for each user where normal and shear stimuli create the same intensity on the user's skin.