1D Printing of Recyclable Robots

Cellucci, Daniel; MacCurdy, Robert; Lipson, Hod; Risi, Sebastian

doi:10.1109/lra.2017.2716418

Cited by 26 publications

(20 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, simulations are often used to weed out undesirable designs before attempting to build them in reality. [43,[58][59][60] Yet, under realistic design conditions, simulations cannot exhaustively search the design space. Even using a small number of mechanical parts, the size of the design space is enormous.…”

Section: Simulated Shape Changing Robotsmentioning

confidence: 99%

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization

et al. 2020

View full text Add to dashboard Cite

are specialized for a single task, and cannot adapt their body to accomplish additional tasks after manufacture. Moreover, biological bodies are often highly regenerative, and able to repair and reconfigure their large-scale architecture in the face of significant damage or radical changes to their components. [3] For example, salamanders regenerate amputated limbs, [4] and fragments cut from arbitrary portions of planaria flatworms can rebuild (and rescale) their bodies to recover a full, correct anatomy. [3] Remarkably, many of these systems are able to retain information, such as learned memories, despite drastic reconfiguration or total replacement of their brains. [5] In these integrated living systems, intelligence, memory, learning, behavior, and body structure are all intertwined and emerge from the multiscale dynamics of the same robust and highly fault-tolerant medium.Evolution did not result in hard-coded body plans purely determined by genetic factors, but rather produced diverse examples of intelligent self-modifying systems which adapt to numerous extragenomic influences. [6] In this way, biology serves as an important proof-of-principle, and design challenge, for artificial intelligence and shape changing robots. Despite having access to this extensive set of model systems, the realization of general-purpose, adaptive robots has remained elusive. Researchers have proposed modular robots that can be attached to each other to expand functionality, [7] passively conforming universal grippers, [8] reconfigurable robotic skins, [9] self-assembling robot swarms, [10] gait-switching mechanisms [11] and controllers, [12,13] and algorithms that quickly re-adapt to multiple distinct tasks. [14] Such approaches succeed at adaptation but operate under the assumption that the robot's body is only reconfigured or reshaped due to external forces, and do not explore the possibility of synthetic machines that actively grow, regenerate, deform, or otherwise change the resting shape of their constituent components.With the introduction of a conformable gripper by Hirose in 1978, [15] followed by continuum robot arms, [16] silicone grippers, [17] and variable stiffness actuators, [18] robots that can adapt to real-world environments by changing their shape are becoming closer to reality. In particular, the idea of passively conforming around objects during grasping has been quite successful. [17,19,20] Soft robots have shown potential in other applications, including human-robot interaction and exploration, as reviewed by Kim et al., [21] Rus et al., [22] and others. [23,24] For a comprehensive review of the role of deformation in singlefunction soft robots, the reader is referred to Wang et al. [25] One of the key differentiators between biological and artificial systems is the dynamic plasticity of living tissues, enabling adaptation to different environmental conditions, tasks, or damage by reconfiguring physical structure and behavioral control policies. Lack of dynamic plasticity is a significant limitation for a...

show abstract

Section: Simulated Shape Changing Robotsmentioning

confidence: 99%

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization

et al. 2020

View full text Add to dashboard Cite

show abstract

“…5 Perhaps the best known physics engine for deformable bodies is Voxelyze, 6 a voxel-based representation that has been used for a large number of soft robotics studies [9,39,57,59] and has become a benchmark on which different design optimization methods are tested (Figure 2(f ), 2(h), for example). A recent GPU-accelerated re-implementation of Voxelyze, voxcraft-sim, 7 has recently been released.…”

Section: Physics Engines and Simulatorsmentioning

confidence: 99%

Reality-Assisted Evolution of Soft Robots through Large-Scale Physical Experimentation: A Review

et al. 2020

View full text Add to dashboard Cite

We introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. In silico, data-driven models build, adapt, and improve representations of the target system using real-world experimental data. By simulating huge numbers of virtual robots using these data-driven models, optimization algorithms can illuminate multiple design candidates for transference to the real world. In reality, large-scale physical experimentation facilitates the fabrication, testing, and analysis of multiple candidate designs. Automated assembly and reconfigurable modular systems enable significantly higher numbers of real-world design evaluations than previously possible. Large volumes of ground-truth data gathered via physical experimentation can be returned to the virtual environment to improve data-driven models and guide optimization. Grounding the design process in physical experimentation ensures that the complexity of virtual robot designs does not outpace the model limitations or available fabrication technologies. We outline key developments in the design of physically embodied soft robots in the framework of reality-assisted evolution.

show abstract

“…Although the resulting robots have modest functionality, this research points towards expandable robotics that rapidly fabricate customized robots on demand and allow robots recycling to produce new robotic designs that can perform new tasks [64].…”

Section: Current State Of the Artmentioning

confidence: 99%

Evolutionary Modular Robotics: Survey and Analysis

Alattas

Patel

Sobh

2018

J Intell Robot Syst

View full text Add to dashboard Cite

This paper surveys various applications of artificial evolution in the field of modular robots. Evolutionary robotics aims to design autonomous adaptive robots automatically that can evolve to accomplish a specific task while adapting to environmental changes. A number of studies have demonstrated the feasibility of evolutionary algorithms for generating robotic control and morphology. However, a huge challenge faced was how to manufacture these robots. Therefore, modular robots were employed to simplify robotic evolution and their implementation in real hardware. Consequently, more research work has emerged on using evolutionary computation to design modular robots rather than using traditional hand design approaches in order to avoid cognition bias. These techniques have the potential of developing adaptive robots that can achieve tasks not fully understood by human designers. Furthermore, evolutionary algorithms were studied to generate global modular robotic behaviors including; self-assembly, self-reconfiguration, self-repair, and self-reproduction. These characteristics allow modular robots to explore unstructured and hazardous environments. In order to accomplish the aforementioned evolutionary modular robotic promises, this paper reviews current research on evolutionary robotics and modular robots. The motivation behind this work is to identify the most promising methods that can lead to developing autonomous adaptive robotic systems that require the minimum task related knowledge on the designer side.

show abstract

1D Printing of Recyclable Robots

Cited by 26 publications

References 44 publications

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization

Reality-Assisted Evolution of Soft Robots through Large-Scale Physical Experimentation: A Review

Evolutionary Modular Robotics: Survey and Analysis

Contact Info

Product

Resources

About