Modular robotics holds immense potential for space exploration, where reliability, repairability, and reusability are critical for cost-effective missions. Coordination between heterogeneous units is paramount for precision tasks -- whether in manipulation, legged locomotion, or multi-robot interaction. Such modular systems introduce challenges far exceeding those in monolithic robot architectures. This study presents a robust method for synchronizing the trajectories of multiple heterogeneous actuators, adapting dynamically to system variations with minimal system knowledge. This design makes it inherently robot-agnostic, thus highly suited for modularity. To ensure smooth trajectory adherence, the multidimensional state is constrained within a hypersphere representing the allowable deviation. The distance metric can be adapted hence, depending on the task and system under control, deformation of the constraint region is possible. This approach is compatible with a wide range of robotic platforms and serves as a core interface for Motion-Stack, our new open-source universal framework for limb coordination (available at https://github.com/2lian/Motion-Stack ). The method is validated by synchronizing the end-effectors of six highly heterogeneous robotic limbs, evaluating both trajectory adherence and recovery from significant external disturbances.

Abstract--Through the implementation of reconfigurability to achieve flexibility and adaptation to tasks by morphology changes rather than by increasing the number of joints, malleable robots present advantages over traditional serial robot arms in regards to reduced weight, size, and cost. While limited in degrees of freedom (DOF), malleable robots still provide versatility across operations typically served by systems using higher DOF than required by the tasks. In this paper, we present the creation of a 2-DOF malleable robot, detailing the design of joints and malleable link, along with its modelling through forward and inverse kinematics, and a reconfiguration methodology that informs morphology changes based on end effector location-- determining how the user should reshape the robot to enable a task previously unattainable. The recalibration and motion planning for making robot motion possible after reconfiguration are also discussed, and thorough experiments with the prototype to evaluate accuracy and reliability of the system are presented. ECONFIGURABLE robot systems provide several key potential advantages over traditional robots, including of the robot (such as locomotion), albeit with a decrease in increased task versatility by adapting to better suit tasks, the performance for a specific task compared to a specialised and reduced robot cost due to a smaller total number of robot. While the majority of reconfigurable robots are modular, modules, such as links and joints. As such, there has been reconfiguration can also be achieved by locking aspects of significant research into the development of reconfigurable the robot. Examples include directly locking revolute joints to robots, with the most popular approach utilising modularity reduce the DOF of the robot [11], and locking passive cylindrical as the method of reconfiguration, as this allows for the joints carefully positioned to directly vary the Denavit-interchangeability of parts, leading to self-repair [1], [2].

Robot co-design, where the morphology of a robot is optimized jointly with a learned policy to solve a specific task, is an emerging area of research. It holds particular promise for soft robots, which are amenable to novel manufacturing techniques that can realize learned morphologies and actuators. Inspired by nature and recent novel robot designs, we propose to go a step further and explore the novel reconfigurable robots, defined as robots that can change their morphology within their lifetime. We unify morphology change, locomotion, and environment interaction in the same action space, and introduce an appropriate, coarse-to-fine curriculum that enables us to discover policies that accomplish fine-grained control of the resulting robots. We also introduce Ditto-Gym, a comprehensive RL benchmark for reconfigurable soft robots that require fine-grained morphology changes to accomplish the tasks. Finally, we evaluate our proposed coarse-to-fine algorithm on DittoGym and demonstrate robots that learn to change their morphology several times within a sequence, uniquely enabled by our RL algorithm. More results are available at https://dittogym.github.io. Over millions of years, morphologies of species change as a function of evolutionary pressures (Minelli, 2003; Raff, 2012). In robotics, this process of evolution has inspired the task of robot co-design: the joint optimization of a robot's morphology and a control policy that best enable the robot to accomplish a given task (Gupta et al., 2022; Wang et al.; Ha, 2019; Yuan et al., 2021). Yet, in nature, creatures do not only change their morphology over millions of years as a function of evolution. Almost all living beings go through a process of morphology changes even in their lifetime. These changes can be dramatic in magnitude, like when a mighty tree grows from a tiny sapling, but they can also be dramatic in form, like across the many examples of metamorphosis, where frogs, for instance, go through a water-dwelling stage with a tail for propulsion, to then lose their tail and grow legs to live on land (Rose, 2005; Hofmann et al., 2003).

The development of mobile robot platforms for inspection has gained traction in recent years with the rapid advancement in hardware and software. However, conventional mobile robots are unable to address the challenge of operating in extreme environments where the robot is required to traverse narrow gaps in highly cluttered areas with restricted access. This paper presents MIRRAX, a robot that has been designed to meet these challenges with the capability of re-configuring itself to both access restricted environments through narrow ports and navigate through tightly spaced obstacles. Controllers for the robot are detailed, along with an analysis on the controllability of the robot given the use of Mecanum wheels in a variable configuration. Characterisation on the robot's performance identified suitable configurations for operating in narrow environments. The minimum lateral footprint width achievable for stable configuration ($<2^\text{o}$~roll) was 0.19~m. Experimental validation of the robot's controllability shows good agreement with the theoretical analysis. A further series of experiments shows the feasibility of the robot in addressing the challenges above: the capability to reconfigure itself for restricted entry through ports as small as 150mm diameter, and navigating through cluttered environments. The paper also presents results from a deployment in a Magnox facility at the Sellafield nuclear site in the UK - the first robot to ever do so, for remote inspection and mapping.

Recommendation: Read this classic hard sci-fi novel and expand your horizons about robots, teleoperation, and swarms. Stanislaw Lem was one of the most read science fiction authors in the world in his day, especially the 70s and 80s, though not in America because there were rarely translations from his native Polish to English. Lem famously did not like American science fiction, with a very few exceptions. One being Philip K. Dick- and it is no wonder since Lem's 1987 novel Peace on Earth shares many of the same themes that Dick covered: militarization of robots, people losing their memory or not being what they seem, and government conspiracies. In some ways Peace on Earth is like the longer, more detailed, and, actually, *better* version of Dick's 1953 short story Second Variety (which was basis for the Peter Weller movie Screamers). Peace on Earth has a sort of a Battlestar Galatica (reboot) backstory.

A team of EPFL researchers has developed tiny 10-gram robots that are inspired by ants: they can communicate with each other, assign roles among themselves and complete complex tasks together. These reconfigurable robots are simple in structure, yet they can jump and crawl to explore uneven surfaces. The researchers have just published their work in Nature. Individually, ants have only so much strength and intelligence. However, as a colony, they can use complex strategies for achieving sophisticated tasks to survive their larger predators.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Need help preparing a romantic dinner for two? ARMAR will give you a hand.