Functional near-infrared spectroscopy (fNIRS) decoding is a crucial foundation for Brain-Computer Interface (BCI) technology. However, existing methods commonly concentrate on time-frequency features and overlook posi...
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Mobile manipulators for indoor human environments can serve as versatile devices that perform a variety of tasks, yet adoption of this technology has been limited. Reducing size, weight, and cost could facilitate adop...
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ISBN:
(纸本)9781728196817
Mobile manipulators for indoor human environments can serve as versatile devices that perform a variety of tasks, yet adoption of this technology has been limited. Reducing size, weight, and cost could facilitate adoption, but risks restricting capabilities. We present a novel design that reduces size, weight, and cost, while supporting a variety of tasks. The core design consists of a two-wheeled differential-drive mobile base, a lift, and a telescoping arm configured to achieve Cartesian motion at the end of the arm. Design extensions include a 1 degree-of-freedom (DOF) wrist to stow a tool, a 2-DOF dexterous wrist to pitch and roll a tool, and a compliant gripper. We justify our design with anthropometry and mathematical models of static stability. We also provide empirical support from teleoperating and autonomously controlling a commercial robot based on our design (the Stretch RE1 from Hello Robot Inc.) to perform tasks in real homes.
The finding of plausible assembly paths of industrial components is a relevant, actual, but not yet fully resolved research topic. For a fast and robust computation of such paths, rigid body sampling-based motion plan...
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ISBN:
(数字)9781665468589
ISBN:
(纸本)9781665468596;9781665468589
The finding of plausible assembly paths of industrial components is a relevant, actual, but not yet fully resolved research topic. For a fast and robust computation of such paths, rigid body sampling-based motion planning is used. To tackle the problem of unavoidable collisions due to overpressure of components or due to flexible fastening elements, the tolerance of minor collisions is necessary. Tolerating minor collisions always means the manipulation of the configuration space or the direct manipulation of objects in the workspace. These actions enable the computation of assembly paths on industrial data, but they affect (explicitly or implicitly) the shape of the objects and thus the physical plausibility of the computed paths. This makes it important to further analyze the assembly paths. In this paper, we propose a postprocessing method for industrial assembly paths that is based on Position Based Dynamics (PBD) and is able to simulate and optimize given assembly paths. We use the PBD framework to simulate and measure the object deformation along the assembly path. For the optimization of the path, we compare the deformed object to the original rigid object and we apply small corrections to the path that decrease the overall deformation. We show the effectiveness of our approach on an academic dataset that provides industrial disassembly scenarios.
One of the fundamental challenges in realizing the potential of legged robots is generating plans to traverse challenging terrains. Control actions must be carefully selected so the robot will not crash or slip. The h...
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ISBN:
(纸本)9781728196817
One of the fundamental challenges in realizing the potential of legged robots is generating plans to traverse challenging terrains. Control actions must be carefully selected so the robot will not crash or slip. The high dimensionality of the joint space makes directly planning low-level actions from onboard perception difficult, and control stacks that do not consider the low-level mechanisms of the robot in planning are ill-suited to handle fine-grained obstacles. One method for dealing with this is selecting footstep locations based on terrain characteristics. However, incorporating robot dynamics into footstep planning requires significant computation, much more than in the quasi-static case. In this work, we present an LSTMbased planning framework that learns probability distributions over likely footstep locations using both terrain lookahead and the robot's dynamics, and leverages the LSTM's sequential nature to find footsteps in linear time. Our framework can also be used as a module to speed up sampling-based planners. We validate our approach on a simulated one-legged hopper over a variety of uneven terrains.
This paper introduces a design method for an efficient and agile quadruped robot. A mixed-integer optimization formulation including the number of gear teeth is derived to obtain the optimal gear ratio that minimizes ...
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ISBN:
(纸本)9781728196817
This paper introduces a design method for an efficient and agile quadruped robot. A mixed-integer optimization formulation including the number of gear teeth is derived to obtain the optimal gear ratio that minimizes cost for a running-trot with the target speed of 3 m/s. With the inclusion of integer constraints related to the number of gear teeth, detailed design considerations of gear trains can be included in the optimization process. Thermal dissipation of the motor controller is also taken into account in the optimization to consider heat generation during high-speed running. KAIST Hound, a 45 kg robot, designed with the obtained design parameters has successfully demonstrated a 3 m/s running-trot using a nonlinear model predictive controller (NMPC). Furthermore, the robot has proved its robustness by the demonstration of additional experiments such as 22 degrees slope climbing, 3.2 km walking, and traversing a 35 cm obstacle.
Learning performant robot manipulation policies can be challenging due to high-dimensional continuous actions and complex physics-based dynamics. This can be alleviated through intelligent choice of action space. Oper...
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ISBN:
(纸本)9781728196817
Learning performant robot manipulation policies can be challenging due to high-dimensional continuous actions and complex physics-based dynamics. This can be alleviated through intelligent choice of action space. Operational Space Control (OSC) has been used as an effective taskspace controller for manipulation. Nonetheless, its strength depends on the underlying modeling fidelity, and is prone to failure when there are modeling errors. In this work, we propose OSC for Adaptation and Robustness (OSCAR), a data-driven variant of OSC that compensates for modeling errors by inferring relevant dynamics parameters from online trajectories. OSCAR decomposes dynamics learning into task-agnostic and task-specific phases, decoupling the dynamics dependencies of the robot and the extrinsics due to its environment. This structure enables robust zero-shot performance under out-of-distribution and rapid adaptation to significant domain shifts through additional finetuning. We evaluate our method on a variety of simulated manipulation problems, and find substantial improvements over an array of controller baselines. For more results and information, please visit https://***/oscar-web/.
This research work aims to analyze and understand the impact of Robotic Process automation (RPA) on businesses across various sectors in Industry 4.0 especially during and after the pandemic. Qualitative primary resea...
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Automatic disassembly planning for complex industrial products like vehicles checks the expandability of components already at early stages of design. For a fast computation of collision-free disassembly paths, sampli...
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ISBN:
(纸本)9781728196817
Automatic disassembly planning for complex industrial products like vehicles checks the expandability of components already at early stages of design. For a fast computation of collision-free disassembly paths, sampling-based rigid body motion planning is used in the literature. However, in real-world scenarios there are circumstances that prevent the finding of plausible collision-free disassembly paths with these conventional motion planners. The most difficult problem is that many components have deformable fastening elements that are modeled in a relaxed state and often as a part of the rigid object. The fastening elements cause unavoidable collisions of the component with its environment along the actual disassembly path. In this paper, we present Iterative Mesh Modification Planning (IMMP). Given the information about fastening elements in advance, our method applies a controlled iterative process of geometric deformations and planning attempts to the component to be disassembled. With this process, we are able to disassemble the component from its installed position with a conventional rigid body motion planner taking fastening elements and also overpressure into account. We demonstrate the effectiveness of our method on real-world planning scenarios from the automotive industry.
Industry 4.0 integrates advanced technologies, digitization, and automation into traditional industrial environments to maximize efficiency and competitiveness in manufacturing enterprises. This concept connects physi...
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ISBN:
(纸本)9798350361506;9798350361490
Industry 4.0 integrates advanced technologies, digitization, and automation into traditional industrial environments to maximize efficiency and competitiveness in manufacturing enterprises. This concept connects physical manufacturing systems with digital technologies by implementing technologies such as the Internet of Things (IoT), advanced robotics, and artificial intelligence (AI). The realization of these goals requires qualified personnel who must be equipped with the necessary technical knowledge and practical skills. For these technologies to be used effectively, it is necessary to train students properly. One of the innovative approaches to teaching the principles of Industry 4.0 is the use of modular models and kits that allow the simulation of real production situations without the risk of operational errors. These models often include advanced technologies such as virtual reality (VR) or augmented reality (AR) to create realistic environments for simulating complex processes. As part of this approach, an automated production line to assemble LEGO cars was developed. This long-term project uses LEGO Technics as the construction platform and LEGO Mindstorms to control electronics and software. Its main goal is to develop a comprehensive educational system per OECD recommendations for teaching Industry 4.0 concepts. This educational system enables the simulation of various types of problems that may occur on the production line (mechanical, electrical, process-related) and in the operational software, providing a comprehensive platform for practicing solving real manufacturing scenarios.
Recent works in Reinforcement Learning (RL) combine model-free (Mf)-RL algorithms with model-based (Mb)-RL approaches to get the best from both: asymptotic performance of Mf-RL and high sample-efficiency of Mb-RL. Ins...
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ISBN:
(纸本)9781728196817
Recent works in Reinforcement Learning (RL) combine model-free (Mf)-RL algorithms with model-based (Mb)-RL approaches to get the best from both: asymptotic performance of Mf-RL and high sample-efficiency of Mb-RL. Inspired by these works, we propose a hierarchical framework that integrates online learning for the Mb-trajectory optimization with off-policy methods for the Mf-RL. In particular, two loops are proposed, where the Dynamic Mirror Descent based Model Predictive Control (DMD-MPC) is used as the inner loop Mb-RL to obtain an optimal sequence of actions. These actions are in turn used to significantly accelerate the outer loop Mf-RL. We show that our formulation is generic for a broad class of MPC based policies and objectives, and includes some of the well-known Mb-Mf approaches. We finally introduce a new algorithm: Mirror-Descent Model Predictive RL (M-DeMoRL), which uses Cross-Entropy Method (CEM) with elite fractions for the inner loop. Our experiments show faster convergence of the proposed hierarchical approach on benchmark MuJoCo tasks. We also demonstrate hardware training for trajectory tracking in a 2R leg, and hardware transfer for robust walking in a quadruped. We show that the inner-loop Mb-RL significantly decreases the number of training iterations required in the hardware setting, thereby validating the proposed approach.
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