-
公开(公告)号：US20210004647A1
公开(公告)日：2021-01-07
申请号：US16920598
申请日：2020-07-03
摘要： Methods and systems of training RL agent for autonomous operation of a vehicle are described. The RL agent is trained using uniformly sampled training samples and learning a policy. After the RL agent has achieved a predetermined performance goal, data is collected including a sequence of sampled states, and for each sequence of sampled states, agent parameters, and an indication of failure of the RL agent for the sequence. A failure predictor is trained, using samples from the collected data, to predict a probability of failure of the RL agent for a given sequence of states. Sequences of states are collected by simulating interaction of the vehicle with the environment. Based on a probability of failure outputted by the failure predictor, a sequence of states is selected. The RL agent is further trained based on the selected sequence of states.
-
2.发明申请公开(公告)号：US20210276598A1
公开(公告)日：2021-09-09
申请号：US16810552
申请日：2020-03-05
摘要： A system and method for path and/or motion planning and for training such a system are described. In one aspect, the method comprises generating a sequence of predicted occupancy grid maps (OGMs) for T-T1 time steps based on a sequence of OGMs for 0-T1 time steps, a reference map of an environment in which an autonomous vehicle is operating, and a trajectory. A cost volume is generated for the sequence of predicted OGMs. The cost volume comprises a plurality of cost maps for T-T1 time steps. Each cost map corresponds to a predicted OGM in the sequence of predicted OGMs and has the same dimensions as the corresponding predicted OGM. Each cost map comprises a plurality of cells.
Each cell in the cost map represents a cost of the cell in corresponding predicted OGM being occupied in accordance with a policy defined by a policy function.-
公开(公告)号：US20210312225A1
公开(公告)日：2021-10-07
申请号：US16840319
申请日：2020-04-03
摘要： A method for generation of an augmented point cloud with point features from aggregated 3D coordinate data and related device. The method comprises receiving a current point cloud in the form of 3D coordinate data in ego coordinates from one or more detection and ranging (DAR) devices of a vehicle. Features are extracted from the current point cloud. A previous point cloud is transformed into ego coordinates using a current location of the vehicle. Each point in the previous point cloud is transformed to align with a corresponding point in the current point cloud to generate a transformed point cloud. The current point cloud is aggregated with the transformed point cloud to generate an aggregated point cloud. The current point features are aggregated with the point features of the transformed point cloud to generate aggregated point features.
-
公开(公告)号：US20210097386A1
公开(公告)日：2021-04-01
申请号：US16890981
申请日：2020-06-02
摘要： Method or system for reinforcement learning that simultaneously learns a DR distribution ϕ while optimizing an agent policy Π to maximize performance over the learned DR distribution; method or system for training a learning agent using data synthesized by a simulator based on both a performance of the learning agent and a range of parameters present in the synthesized data.
-
公开(公告)号：US20200090357A1
公开(公告)日：2020-03-19
申请号：US16568885
申请日：2019-09-12
摘要： Methods and systems for generating synthetic point cloud data are described. Projected 2D data grid is generated by projecting a 3D point cloud into a 2D grid, with rotation equivariance. A generative model is learned using the projected 2D data grid, wherein the generative model is implemented using flex-convolution and transpose flex convolution operations, for example in a generative adversarial network. The learned generative model is used to generate synthetic point clouds.
-
-
-
-
搜索结果
5 条记录 (耗时 0.016 秒)
