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Recent progress in reinforcement learning (RL) and tactile sensing has significantly advanced dexterous manipulation. However, these methods often utilize simplified tactile signals due to the gap between tactile simulation and the real world. We introduce a sensor model for tactile skin that enables zero-shot sim-to-real transfer of ternary shear and binary normal forces. Using this model, we develop an RL policy that leverages sliding contact for dexterous in-hand translation. We conduct extensive real-world experiments to assess how tactile sensing facilitates policy adaptation to various unseen object properties and robot hand orientations. We demonstrate that our 3-axis tactile policies consistently outperform baselines that use only shear forces, only normal forces, or only proprioception. Website: https://jessicayin.github.io/tactile-skin-rl/, Comment: Website: https://jessicayin.github.io/tactile-skin-rl/

Communication and position sensing are among the most important capabilities for swarm robots to interact with their peers and perform tasks collaboratively. However, the hardware required to facilitate communication and position sensing is often too complicated, expensive, and bulky to be carried on swarm robots. Here we present Maneuverable Piccolissimo 3 (MP3), a minimalist, single motor drone capable of executing inter-robot communication via infrared light and triangulation-based sensing of relative bearing, distance, and elevation using message arrival time. Thanks to its novel design, MP3 can communicate with peers and localize itself using simple components, keeping its size and mass small and making it inherently safe for human interaction. We present the hardware and software design of MP3 and demonstrate its capability to localize itself, fly stably, and maneuver in the environment using peer-to-peer communication and sensing.

Despite their growing popularity, swarms of robots remain limited by the operating time of each individual. We present algorithms which allow a human to sculpt a swarm of robots into a shape that persists in space perpetually, independent of onboard energy constraints such as batteries. Robots generate a path through a shape such that robots cycle in and out of the shape. Robots inside the shape react to human initiated changes and adapt the path through the shape accordingly. Robots outside the shape recharge and return to the shape so that the shape can persist indefinitely. The presented algorithms communicate shape changes throughout the swarm using message passing and robot motion. These algorithms enable the swarm to persist through any arbitrary changes to the shape. We describe these algorithms in detail and present their performance in simulation and on a swarm of mobile robots. The result is a swarm behavior more suitable for extended duration, dynamic shape-based tasks in applications such as agriculture and emergency response., Comment: 20 pages, 17 figures

Micro aerial vehicles are making a large impact in applications such as search-and-rescue, package delivery, and recreation. Unfortunately, these diminutive drones are currently constrained to carrying small payloads, in large part because they use propellers optimized for larger aircraft and inviscid flow regimes. Fully realizing the potential of emerging microflyers requires next-generation propellers that are specifically designed for low-Reynolds number conditions and that include new features advantageous in highly viscous flows. One aspect that has received limited attention in the literature is the addition of roughness to propeller blades as a method of reducing drag and increasing thrust. To investigate this possibility, we used large eddy simulation to conduct a numerical investigation of smooth and rough propellers. Our results indicate that roughness produces a 2% increase in thrust and a 5% decrease in power relative to a baseline smooth propeller operating at the same Reynolds number of Rec = 6500, held constant by rotational speed. We corroborated our numerical findings using thrust-stand-based experiments of 3D-printed propellers identical to those of the numerical simulations. Our study confirms that surface roughness is an additional parameter within the design space for micro-propellers that will lead to unprecedented drone efficiencies and payloads., Comment: 23 Pages, 9 Figures

The Modboat is a low-cost, underactuated, modular robot capable of surface swimming, docking to other modules, and undocking from them using only a single motor and two passive flippers. Undocking is achieved by causing intentional self-collision between the tails of neighboring modules in certain configurations; this becomes a challenge, however, when collective swimming as one connected component is desirable. Prior work has developed controllers that turn arbitrary configurations of docked Modboats into steerable vehicles, but they cannot counteract lateral forces and disturbances. In this work we present a centralized control strategy to create holonomic vehicles out of arbitrary configurations of docked Modboats using an iterative potential-field based search. We experimentally demonstrate that our controller performs well and can control surge and sway velocities and yaw angle simultaneously.

Soft robotic actuators are safe and adaptable devices with inherent compliance, which makes them attractive for manipulating delicate and complex objects. Researchers have integrated stiff materials into soft actuators to increase their force capacity and direct their deformation. However, these embedded materials have largely been pre-prescribed and static, which constrains the actuators to a predetermined range of motion. In this work, electroadhesive (EA) clutches integrated on a single-chamber soft pneumatic actuator (SPA) provide local programmable stiffness modulation to control the actuator deformation. We show that activating different clutch patterns inflates a silicone membrane into pyramidal, round, and plateau shapes. Curvatures from these shapes are combined during actuation to apply forces on both a 3.7 g and 820 g object along five different degrees of freedom (DoF). The actuator workspace is up to 12 mm for light objects. Clutch deactivation, which results in local elastomeric expansion, rapidly applies forces up to 3.2 N to an object resting on the surface and launches a 3.7 g object in controlled directions. The actuator also rotates a heavier, 820 g, object by 5 degrees and rapidly restores it to horizontal alignment after clutch deactivation. This actuator is fully powered by a 5 V battery, AA battery, DC-DC transformer, and 4.5 V (63 g) DC air pump. These results demonstrate a first step towards realizing a soft actuator with high DoF shape change that preserves the inherent benefits of pneumatic actuation while gaining the electrical controllability and strength of EA clutches. We envision such a system supplying human contact forces in the form of a low-profile sit-to-stand assistance device, bed-ridden patient manipulator, or other ergonomic mechanism. This technology was also demonstrated at ICRA 2022: https://www.youtube.com/watch?v=6Y6-iHWNi6s, Comment: This work was presented at IEEE International Conference on Intelligent Robots and Systems (IROS) 2022

The Modboat is a low-cost, underactuated, modular robot capable of surface swimming, docking to other modules, and undocking from them using only a single motor and two passive flippers. Undocking is achieved by causing intentional self-collision between the tails of neighboring modules in certain configurations; this becomes a challenge, however, when collective swimming as one connected component is desirable. In this work, we develop a centralized control strategy to allow \textit{arbitrary} configurations of Modboats to swim as a single steerable vehicle and guarantee no accidental undocking. We also present a simplified model for hydrodynamic interactions between boats in a configuration that is tractable for real-time control. We experimentally demonstrate that our controller performs well, is consistent for configurations of various sizes and shapes, and can control both surge velocity and yaw angle simultaneously. Controllability is maintained while swimming, but pure yaw control causes lateral movement that cannot be counteracted by the presented framework., Comment: 11 pages. Submitted for consideration in the IEEE Transactions on Robotics (T-RO)

The most common sensing modalities found in a robot perception system are vision and touch, which together can provide global and highly localized data for manipulation. However, these sensing modalities often fail to adequately capture the behavior of target objects during the critical moments as they transition out of static, controlled contact with an end-effector to dynamic and uncontrolled motion. In this work, we present a novel multimodal visuotactile sensor that provides simultaneous visuotactile and proximity depth data. The sensor integrates an RGB camera and air pressure sensor to sense touch with an infrared time-of-flight (ToF) camera to sense proximity by leveraging a selectively transmissive soft membrane to enable the dual sensing modalities. We present the mechanical design, fabrication techniques, algorithm implementations, and evaluation of the sensor's tactile and proximity modalities. The sensor is demonstrated in three open-loop robotic tasks: approaching and contacting an object, catching, and throwing. The fusion of tactile and proximity data could be used to capture key information about a target object's transition behavior for sensor-based control in dynamic manipulation., Comment: Accepted to IEEE International Conference on Soft Robotics (RoboSoft) 2022

The Modboat is a low-cost, underactuated, modular robot capable of surface swimming. It is able to swim individually, dock to other Modboats, and undock from them using only a single motor and two passive flippers. Undocking without additional actuation is achieved by causing intentional self-collision between the tails of neighboring modules; this becomes a challenge when group swimming as one connected component is desirable. In this work, we develop a control strategy to allow parallel lattices of Modboats to swim as a single unit, which conventionally requires holonomic modules. We show that the control strategy is guaranteed to avoid unintentional undocking and minimizes internal forces within the lattice. Experimental verification shows that the controller performs well and is consistent for lattices of various sizes. Controllability is maintained while swimming, but pure yaw control causes lateral movement that cannot be counteracted by the presented framework., Comment: 7 pages. Accepted to the 2022 International Conference on Robotics and Automation (ICRA)

Accurate position sensing is important for state estimation and control in robotics. Reliable and accurate position sensors are usually expensive and difficult to customize. Incorporating them into systems that have very tight volume constraints such as modular robots are particularly difficult. PaintPots are low-cost, reliable, and highly customizable position sensors, but their performance is highly dependent on the manufacturing and calibration process. This paper presents a Kalman filter with a simplified observation model developed to deal with the non-linearity issues that result in the use of low-cost microcontrollers. In addition, a complete solution for the use of PaintPots in a variety of sensing modalities including manufacturing, characterization, and estimation is presented for an example modular robot, SMORES-EP. This solution can be easily adapted to a wide range of applications., Comment: 10 pages, 28 figures

This paper develops a decentralized approach to mobile sensor coverage by a multi-robot system. We consider a scenario where a team of robots with limited sensing range must position itself to effectively detect events of interest in a region characterized by areas of varying importance. Towards this end, we develop a decentralized control policy for the robots -- realized via a Graph Neural Network -- which uses inter-robot communication to leverage non-local information for control decisions. By explicitly sharing information between multi-hop neighbors, the decentralized controller achieves a higher quality of coverage when compared to classical approaches that do not communicate and leverage only local information available to each robot. Simulated experiments demonstrate the efficacy of multi-hop communication for multi-robot coverage and evaluate the scalability and transferability of the learning-based controllers.

Hardware platforms for socially interactive robotics can be limited by cost or lack of functionality. This paper presents the overall system -- design, hardware, and software -- for Quori, a novel, affordable, socially interactive humanoid robot platform for facilitating non-contact human-robot interaction (HRI) research. The design of the system is motivated by feedback sampled from the HRI research community. The overall design maintains a balance of affordability and functionality. Initial Quori testing and a six-month deployment are presented. Ten Quori platforms have been awarded to a diverse group of researchers from across the United States to facilitate HRI research to build a community database from a common platform., Comment: 20 pages. 21 figures. This was accepted to and will be published to the IEEE Transactions on Robotics Journal

Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by not only controlling joint positions as with fixed morphology robots, but also reconfiguring the connectivity between truss members in order to change their topology. The motion planning problem for VTT robots is difficult due to their varying morphology, high dimensionality, the high likelihood for self-collision, and complex motion constraints. In this paper, a new motion planning framework to dramatically alter the structure of a VTT is presented. It can also be used to solve locomotion tasks that are much more efficient compared with previous work. Several test scenarios are used to show its effectiveness. Supplementary materials are available at https://www.modlabupenn.org/vtt-motion-planning/., Comment: 20 pages, 36 figures

The Modboat is an autonomous surface robot that turns the oscillation of a single motor into a controlled paddling motion through passive flippers. Inertial control methods developed in prior work can successfully drive the Modboat along trajectories and enable docking to neighboring modules, but have a non-constant cycle time and cannot react to dynamic environments. In this work we present a thrust direction control method for the Modboat that significantly improves the time-response of the system and increases the accuracy with which it can be controlled. We experimentally demonstrate that this method can be used to perform more compact maneuvers than prior methods or comparable robots can. We also present an extension to the controller that solves the reaction wheel problem of unbounded actuator velocity, and show that it further improves performance., Comment: 6 pages. Published in and presented at the 2021 IEE/RSJ International Conference on Intelligent Robots and Systems

Motion planning in high-dimensional space is a challenging task. In order to perform dexterous manipulation in an unstructured environment, a robot with many degrees of freedom is usually necessary, which also complicates its motion planning problem. Real-time control brings about more difficulties in which robots have to maintain the stability while moving towards the target. Redundant systems are common in modular robots that consist of multiple modules and are able to transformed into different configurations with respect to different needs. Different from robots with fixed geometry or configurations, the kinematics model of a modular robotic system can alter as the robot reconfigures itself, and developing a generic control and motion planning approach for such systems is difficult, especially when multiple motion goals are coupled. A new manipulation planning framework is developed in this paper. The problem is formulated as a sequential linearly constrained quadratic program (QP) that can be solved efficiently. Some constraints can be incorporated into this QP, including a novel way to approximate environment obstacles. This solution can be used directly for real-time applications or as an off-line planning tool, and it is validated and demonstrated on the CKBot and SMORES-EP modular robot platforms., Comment: 25 pages, 20 figures

Self-assembly of modular robotic systems enables the construction of complex robotic configurations to adapt to different tasks. This paper presents a framework for SMORES types of modular robots to efficiently self-assemble into tree topologies. These modular robots form kinematic chains that have been shown to be capable of a large variety of manipulation and locomotion tasks, yet they can reconfigure using a mobile reconfiguration. A desired kinematic topology can be mapped onto a planar pattern with optimal module assignment based on the modules' locations, then the mobile reconfiguration assembly process can be executed in parallel. A docking controller is developed to guarantee the success of docking processes. A hybrid control architecture is designed to handle a large number of modules and complex behaviors of each individual, and achieve efficient and robust self-assembly actions. The framework is demonstrated in both hardware and simulation on the SMORES-EP platform., Comment: 18 pages, 20 figures. Auton Robot (2022)

We describe a docking mechanism and strategy to allow modular self-assembly for the Modboat: an inexpensive underactuated oscillating swimming robot powered by a single motor. Because propulsion is achieved through oscillation, orientation can be controlled only in the average; this complicates docking, which requires precise position and orientation control. Given these challenges, we present a docking strategy and a motion primitive for controlling orientation, and show that this strategy allows successful docking in multiple configurations. Moreover, we demonstrate that the Modboat is also capable of undocking and changing its dock configuration, all without any additional actuation. This is unique among similar modular robotic systems., Comment: 6 pages. Submitted to the 2021 IEEE International Conference on Robotics and Automation (ICRA)

We present a novel design for a low-cost robotic boat powered by a single actuator, useful for both modular and swarming applications. The boat uses the conservation of angular momentum and passive flippers to convert the motion of a single motor into an adjustable paddling motion for propulsion and steering. We develop design criteria for modularity and swarming and present a prototype implementing these criteria. We identify significant mechanical sensitivities with the presented design, theorize about the cause of the sensitivities, and present an improved design for future work., Comment: Accepted to the International Conference on Ubiquitous Robots (UR 2020). 8 pages

Building structures can allow a robot to surmount large obstacles, expanding the set of areas it can reach. This paper presents a planning algorithm to automatically determine what structures a construction-capable robot must build in order to traverse its entire environment. Given an environment, a set of building blocks, and a robot capable of building structures, we seek a optimal set of structures (using a minimum number of building blocks) that could be built to make the entire environment traversable with respect to the robot's movement capabilities. We show that this problem is NP-Hard, and present a complete, optimal algorithm that solves it using a branch-and-bound strategy. The algorithm runs in exponential time in the worst case, but solves typical problems with practical speed. In hardware experiments, we show that the algorithm solves 3D maps of real indoor environments in about one minute, and that the structures selected by the algorithm allow a robot to traverse the entire environment. An accompanying video is available online at https://youtu.be/B9WM557NP44.

The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) A high-level mission planner, (2) A large design library spanning a wide set of functionality, (3) A design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by the authors, extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system., Comment: Published in Autonomous Robots, 2018. 18 pages

We present a system enabling a modular robot to autonomously build structures in order to accomplish high-level tasks. Building structures allows the robot to surmount large obstacles, expanding the set of tasks it can perform. This addresses a common weakness of modular robot systems, which often struggle to traverse large obstacles. This paper presents the hardware, perception, and planning tools that comprise our system. An environment characterization algorithm identifies features in the environment that can be augmented to create a path between two disconnected regions of the environment. Specially-designed building blocks enable the robot to create structures that can augment the environment to make obstacles traversable. A high-level planner reasons about the task, robot locomotion capabilities, and environment to decide if and where to augment the environment in order to perform the desired task. We validate our system in hardware experiments, Comment: 2018 IEEE International Conference on Robotics and Automation (ICRA). 7 pages

The theoretical ability of modular robots to reconfigure in response to complex tasks in a priori unknown environments has frequently been cited as an advantage and remains a major motivator for work in the field. We present a modular robot system capable of autonomously completing high-level tasks by reactively reconfiguring to meet the needs of a perceived, a priori unknown environment. The system integrates perception, high-level planning, and modular hardware, and is validated in three hardware demonstrations. Given a high-level task specification, a modular robot autonomously explores an unknown environment, decides when and how to reconfigure, and manipulates objects to complete its task. The system architecture balances distributed mechanical elements with centralized perception, planning, and control. By providing an example of how a modular robot system can be designed to leverage reactive reconfigurability in unknown environments, we have begun to lay the groundwork for modular self-reconfigurable robots to address tasks in the real world., Comment: Published article available at: http://robotics.sciencemag.org/cgi/content/full/3/23/eaat4983?ijkey=iBq7yW7Z8vmjE&keytype=ref&siteid=robotics