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Today, robots can be found helping humans with their daily tasks. Some tasks require the robot to visit a set of locations in the environment efficiently, like in the Traveling Salesman Problem. As indoor environments are maze-like areas, feasible paths connecting locations must be computed beforehand, so they can be combined during the scheduling, which can be impracticable for real-time applications. This work presents an on-line Route Scheduling supported by a Fast Path Planning Method able to adjust pre-built paths. Experiments were carried out with virtual and real robots to evaluate time and quality of tours.
Modules are requisite for the realization of modular reconfigurable manipulators. The design of modules in literature mainly revolves around geometric aspects and features such as lengths, connectivity and adaptivity. Optimizing and designing the modules based on dynamic performance is considered as a challenge here. The present paper introduces an Architecture-Prominent-Sectioning (APS) strategy for the planning of architecture of modules such that a reconfigurable manipulator possesses minimal joint torques during its operations. Proposed here is the transferring of complete structure into an equivalent system, perform optimization and map the resulting arrangement into possible architecture. The strategy has been applied on a set of modular configurations considering three-primitive-paths. The possibility of getting advanced/complex shapes is also discussed to incorporate the idea of a modular library.
To improve the accessibility of robotics, we propose a design and fabrication strategy to build low-cost electromechanical systems for robotic devices. Our method, based on origami-inspired cut-and-fold and E-textiles techniques, aims at minimizing the resources for robot creation. Specifically, we explore techniques to create robots with the resources restricted to single-layer sheets (e.g., polyester film) and conductive sewing threads. To demonstrate our strategy’s feasibility, these techniques are successfully integrated into an electromechanical oscillator (about 0.40 USD), which can generate electrical oscillation under constant-current power and potentially be used as a simple robot controller in lieu of additional external electronics.
We propose a computational design tool to enable casual end-users to easily design, fabricate, and assemble flat-pack furniture with guaranteed manufacturability. Using our system, users select parameterized components from a library and constrain their dimensions. Then they abstractly specify connections among components to define the furniture. Once fabrication specifications (e.g., materials) designated, the mechanical implementation of the furniture is automatically handled by leveraging encoded domain expertise. Afterwards, the system outputs three-dimensional models for visualization and mechanical drawings for fabrication. We demonstrate the validity of our approach by designing, fabricating, and assembling a variety of flat-pack (scaled) furniture on demand.
We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.