Reinforcement Learning (RL), a method of learning skills through trial-and-error, has been successfully used in many robotics applications in recent years. We combine manipulation primitives (MPs), behavior trees (BTs...
详细信息
In this paper, Prioritized Experience Replay (PER) strategy and Long Short Term Memory (LSTM) neural network are introduced to the path planning process of mobile robots, which solves the problems of slow convergence ...
详细信息
In recent years, Deep Reinforcement Learning (DRL) has emerged as a competitive approach for mobile robot navigation. However, training DRL agents often comes at the cost of difficult and tedious training procedures i...
In recent years, Deep Reinforcement Learning (DRL) has emerged as a competitive approach for mobile robot navigation. However, training DRL agents often comes at the cost of difficult and tedious training procedures in which powerful hardware is required to conduct oftentimes long training runs. Especially, for complex environments, this proves to be a major bottleneck for widespread adoption of DRL approaches into industries. In this paper we integrate an efficient 2D simulator into the Arena-Rosnav framework of our previous work as an alternative simulation platform to train and develop DRL agents. Therefore, we utilized the provided API to integrate necessary components into the ecosystem of Arena-Rosnav. We evaluated our simulator by training a DRL agent within that platform and compared the training and navigational performance against the baseline 2D simulator Flatland, which is the default simulating platform of Arena-Rosnav. Results demonstrate that using our Arena2D simulator results in substantially faster training times and in some scenarios better agents. This proves to be an important step towards resource-efficient DRL training, which accelerates training times and improve the development cycle of DRL agents for navigation tasks. We made our simulator openly available at https://***/Arena-Rosnav/arena2d.
The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Differ...
详细信息
The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Different control strategies have been reported to compensate the effects of time delay in the communication channel;however, most of them result in poor performance under data loss. First, a model for data loss is proposed using a finite series representation of a set of periodic continuous *** improve the performance and data reconstruction, a holder circuits is also introduced. The passivity of the overall system is provided via the wave variable technique based on the proposed model for the data loss. The stability analysis of the system is then derived using the Lyapunov theorem under the time delay and the data loss. Finally, experimental results are given to illustrate the capability of the proposed control technique.
In the application scenario of robot autonomous tasks, the robot needs to be able to complete calibration online and automatically to achieve self-maintenance, which differs from traditional robot hand-eye calibration...
详细信息
In this paper, a general Gray code quantized method of binary feature descriptors is proposed for fast and efficient keypoint matching on 3D point clouds. In our method, it includes 2 variable L and N. L is rule varia...
详细信息
In this paper, a general Gray code quantized method of binary feature descriptors is proposed for fast and efficient keypoint matching on 3D point clouds. In our method, it includes 2 variable L and N. L is rule variable which can be used to set the encoding group length according to the feature of the real-valued descriptor, and N is bits variable which can be used to set the number of Gray code bits according to the actual system requirements. Be different from the exist method, such as B-SHOT, our proposed method has the advantages of reasonable and flexible. As an example, our method is applied on the feature descriptor SHOT and tested in a standard benchmark dataset, different variable combinations of L and N are tested in the Gray code quantized processes, the best combination of L and N is dubbed as GRAY-SHOT through performance comparison. At last, GRAY-SHOT is compared with the state-of-the-art binary 3D feature descriptor B-SHOT, experimental evaluation result shows that GRAY-SHOT offers better keypoint matching performances to B-SHOT on a standard benchmark dataset with a slight more memory footprint and time consumption.
We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the uniq...
详细信息
The goal of the system presented in this paper is to support several facial surgeries that are aiming to transform an unsymmetrical face to a symmetric one. There are two main techniques to achieve this goal: distract...
详细信息
We introduce a method to apply a preoperative 3D plan for inserting dental implants with an assisting medical robot. The treatment plan is based on the 3D visualization of the CT data of the patient.s maxilla and mand...
详细信息
When planning craniofacial surgical interventions, the ideal appearance of the patient is very important. The final appearance should be as close as possible to that which the patient would have if he/she were without...
详细信息
暂无评论