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1. Closed-Loop Control of Magnetic Modular Cubes for 2D Self-Assembly

   https://doi.org/10.1109/LRA.2023.3296008  

   Lu, Yitong ; Bhattacharjee, Anuruddha ; Taylor, Conlan C. ; Leclerc, Julien ; O'Kane, Jason M. ; Kim, MinJun ; Becker, Aaron T. ( January 2023 , IEEE Robotics and Automation Letters)

   Ani Hsieh (Ed.)

   Reconfigurable modular robots can dynamically assemble/disassemble to accomplish the desired task better. Magnetic modular cubes are scalable modular subunits with embedded permanent magnets in a 3D-printed cubic body and can be wirelessly controlled by an external, uniform, timevarying magnetic field. This paper considers the problem of self-assembling these modules into desired 2D polyomino shapes using such magnetic fields. Although the applied magnetic field is the same for each magnetic modular cube, we use collisions with workspace boundaries to rearrange the cubes. We present a closed-loop control method for self-assembling the magnetic modular cubes into polyomino shapes, using computer vision-based feedback with re-planning. Experimental results demonstrate that the proposed closed-loop control improves the success rate of forming 2D user-specified polyominoes compared to an open-loop baseline. We also demonstrate the validity of the approach over changes in length scales, testing with both 10mm edge length cubes and 2.8mm edge length cubes. 

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2. Enumeration of Polyominoes & Polycubes Composed of Magnetic Cubes

   https://doi.org/10.1109/IROS51168.2021.9636784  

   Lu, Yitong ; Bhattacharjee, Anuruddha ; Biediger, Daniel ; Kim, MinJun ; Becker, Aaron T. ( September 2021 , 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

   This paper examines a family of designs for magnetic cubes and counts how many configurations are possible for each design as a function of the number of modules. Magnetic modular cubes are cubes with magnets arranged on their faces. The magnets are positioned so that each face has either magnetic south or north pole outward. Moreover, we require that the net magnetic moment of the cube passes through the center of opposing faces. These magnetic arrangements enable coupling when cube faces with opposite polarity are brought in close proximity and enable moving the cubes by controlling the orientation of a global magnetic field. This paper investigates the 2D and 3D shapes that can be constructed by magnetic modular cubes, and describes all possible magnet arrangements that obey these rules. We select ten magnetic arrangements and assign a "color" to each of them for ease of visualization and reference. We provide a method to enumerate the number of unique polyominoes and polycubes that can be constructed from a given set of colored cubes. We use this method to enumerate all arrangements for up to 20 modules in 2D and 16 modules in 3D. We provide a motion planner for 2D assembly and through simulations compare which arrangements require fewer movements to generate and which arrangements are more common. Hardware demonstrations explore the self-assembly and disassembly of these modules in 2D and 3D. 

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3. Manipulating deformable objects by interleaving prediction, planning, and control

   https://doi.org/10.1177/0278364920918299  

   McConachie, Dale ; Dobson, Andrew ; Ruan, Mengyao ; Berenson, Dmitry ( June 2020 , The International Journal of Robotics Research)

   We present a framework for deformable object manipulation that interleaves planning and control, enabling complex manipulation tasks without relying on high-fidelity modeling or simulation. The key question we address is when should we use planning and when should we use control to achieve the task? Planners are designed to find paths through complex configuration spaces, but for highly underactuated systems, such as deformable objects, achieving a specific configuration is very difficult even with high-fidelity models. Conversely, controllers can be designed to achieve specific configurations, but they can be trapped in undesirable local minima owing to obstacles. Our approach consists of three components: (1) a global motion planner to generate gross motion of the deformable object; (2) a local controller for refinement of the configuration of the deformable object; and (3) a novel deadlock prediction algorithm to determine when to use planning versus control. By separating planning from control we are able to use different representations of the deformable object, reducing overall complexity and enabling efficient computation of motion. We provide a detailed proof of probabilistic completeness for our planner, which is valid despite the fact that our system is underactuated and we do not have a steering function. We then demonstrate that our framework is able to successfully perform several manipulation tasks with rope and cloth in simulation, which cannot be performed using either our controller or planner alone. These experiments suggest that our planner can generate paths efficiently, taking under a second on average to find a feasible path in three out of four scenarios. We also show that our framework is effective on a 16-degree-of-freedom physical robot, where reachability and dual-arm constraints make the planning more difficult.

    

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4. GAPCoD : A Generic Assembly Planner by Constrained Disassembly

   Pescher, Florian ; Napp, Nils ; Piranda, Benoît ; Bourgeois, Julien ( May 2020 , International Conference On Autonomous Agents and Multi-Agent Systems (AAMAS 2020))

   In the literature we can find many kinds of modular robot that can build a wide variety of structures. In general, finding an assembly order to reach the final configuration, while respecting the insertion constraints of each kind of modular robot is a difficult process that requires system-specific tuning. In this article, we introduce a generic assembly planner by constrained disassembly (GAPCoD) which works with all kinds of modular robots. It outputs a directed acyclic graph where vertices are modules needing to be placed before his child nodes. This graph is obtained through the disassembly of the desired structure submitted to user chosen constraints. We detail the compiler as well as the way to choose constraints and their influence on performance. The robots embed simple path planning algorithm to reach the destination and act as decentralized agents. Examples are provided to show the possibilities that the compiler offers with two very different robot systems and constraints. 

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5. Toward Safety-Aware Informative Motion Planning for Legged Robots

   Teng, Sangli ; Gong, Yukai ; Grizzle, Jessy ; Ghaffari, Maani ( March 2021 , ArXivorg)

   null (Ed.)

   This paper reports on developing an integrated framework for safety-aware informative motion planning suitable for legged robots. The information-gathering planner takes a dense stochastic map of the environment into account, while safety constraints are enforced via Control Barrier Functions (CBFs). The planner is based on the Incrementally-exploring Information Gathering (IIG) algorithm and allows closed-loop kinodynamic node expansion using a Model Predictive Control (MPC) formalism. Robotic exploration and information gathering problems are inherently path-dependent problems. That is, the information collected along a path depends on the state and observation history. As such, motion planning solely based on a modular cost does not lead to suitable plans for exploration. We propose SAFE-IIG, an integrated informative motion planning algorithm that takes into account: 1) a robot’s perceptual field of view via a submodular information function computed over a stochastic map of the environment, 2) a robot’s dynamics and safety constraints via discrete-time CBFs and MPC for closedloop multi-horizon node expansions, and 3) an automatic stopping criterion via setting an information-theoretic planning horizon. The simulation results show that SAFE-IIG can plan a safe and dynamically feasible path while exploring a dense map. 

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