JP2019501468A - 遠隔操作および/またはプランナ決定を最適化するための機械学習システムおよび技法 - Google Patents
遠隔操作および/またはプランナ決定を最適化するための機械学習システムおよび技法 Download PDFInfo
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Abstract
Description
本PCT国際出願は、2015年11月5日に出願された「Machine−Learning Systems and Techniques to Optimize Teleoperation and/or Planner Decisions」と題する米国出願第14/933,602号、2015年11月4日に出願された「Autonomous Vehicle Fleet Service And System」と題する米国特許出願第14/932,959号、2015年11月4日に出願された「Adaptive Mapping To Navigate Autonomous Vehicles Responsive To Physical Environment Changes」と題する米国特許出願第14/932,963号、2015年11月4日に出願された「Teleoperation System And Method For Trajectory Modification Of Autonomous Vehicles」と題する米国特許出願第14/932,966号、および2015年11月4日に出願された「Automated Extraction of Semantic Information to Enhance Incremental Mapping Modifications for Robotic Vehicles」と題する米国特許出願第14/932,940号の継続出願であり、これらのすべては、あらゆる目的のためにそれらの全体が参照により本明細書に組み込まれる。
Claims (10)
- センサまたは通信インターフェースのうちの1つまたは複数から、イベントと関連付けられたテレメトリデータを受信するステップであって、前記イベントは自律車両と関連付けられている、ステップと、
ポリシデータを取得するステップであって、前記ポリシデータは、自律車両を動作させるための命令、および、前記イベントと関連付けられたイベント信頼水準を含み、前記イベント信頼水準は、前記自律車両が、前記ポリシデータに従った動作中に、前記イベントを考慮して安全に動作する確実度を示す、ステップと、
前記テレメトリデータに基づいて、前記イベントに応答して候補軌道を取得するステップであって、各候補軌道は、関連付けられた信頼水準を有する、ステップと、
プロセッサによる機械学習によって、かつ、前記候補軌道および前記テレメトリデータに少なくとも部分的に基づいて、前記ポリシデータに従うのとは異なる方法で、前記イベントに応答して前記自律車両を動作させるための命令を含む、更新されたポリシデータを生成するステップと、
前記更新されたポリシデータを、通信インターフェースを介して少なくとも1つの自律車両に通信するステップと
を含む方法。 - 前記イベント信頼水準は、前記ポリシデータによって指定される信頼水準閾値を満たすことができないことによって、前記自律車両の非規範的な動作状態を示す請求項1に記載の方法。
- 前記更新されたポリシデータを少なくとも1つの自律車両に通信するステップは、前記イベントが関連付けられている前記自律車両以外の自律車両に、前記更新されたポリシデータを通信するステップを含む請求項1に記載の方法。
- テレオペレータコンピューティングデバイスにおいて、前記テレメトリデータが受信され、前記ポリシデータが取得され、前記テレオペレータコンピューティングデバイスは、前記更新されたポリシデータを少なくとも1つの自律車両に通信するように構成されている請求項1に記載の方法。
- シミュレータにおいて、前記テレメトリデータが受信され、前記ポリシデータが取得され、前記方法は、前記シミュレータによって、
前記テレメトリデータまたは前記ポリシデータのうちの1つまたは複数に少なくとも部分的に基づいて前記候補軌道をシミュレートすることによって、前記イベントに応答して前記候補軌道を取得するステップと、
前記シミュレートされている候補軌道と関連付けられた信頼水準を判定するステップと、
前記自律車両による実施のための前記候補軌道のうちの1つの選択を受信するステップと、
前記選択されている軌道を、前記更新されたポリシデータの部分として前記少なくとも1つの自律車両に提供するステップと
をさらに含む請求項5に記載の方法。 - 前記方法は、前記シミュレータによって、
前記候補軌道または前記選択されている軌道のシミュレーションのうちの1つまたは複数に少なくとも部分的に基づいて、前記更新されたポリシデータの前記生成を実行するステップと、
前記ポリシデータまたは前記更新されたポリシデータのうちの1つまたは複数を、
テレオペレータコンピューティングデバイス、または
前記少なくとも1つの自律車両
のうちの1つまたは複数に通信するステップと
をさらに含む請求項6に記載の方法。 - 前記少なくとも1つの自律車両が遠隔操作軌道に従って動作したことを判定するステップと、
前記少なくとも1つの自律車両から、さらなるテレメトリデータを取得するステップと、
少なくとも前記さらなるテレメトリデータから、前記遠隔操作軌道に従った、かつ、前記イベントに応答した前記少なくとも1つの自律車両の動作が、前記少なくとも1つの自律車両の規範的な動作をもたらしたことを判定するステップと、
前記遠隔操作軌道に従って前記少なくとも1つの自律車両を動作させることが、規範的な動作をもたらしたという判定に応答して、前記更新されたポリシを機械学習によって生成するステップと、
前記更新されたポリシデータを、前記少なくとも1つの自律車両に通信するステップと
をさらに含む請求項1に記載の方法。 - 前記ポリシデータは、
前記自律車両を動作させるための候補軌道を選択するための基準、
軌道の生成に対する制約を規定する規則、
前記自律車両の動作が規範的であるか否かを判定するための閾値信頼水準、
前記テレメトリデータから、前記自律車両が動作している環境内のオブジェクトを検出するための分類子、
前記テレメトリデータから検出されるオブジェクトの意味論的な分類、または
前記イベントと関連付けられた意味論的な分類
のうちの1つまたは複数を含み、
前記更新されたポリシデータは、前記基準、前記規則、前記閾値信頼水準、前記オブジェクトの前記意味論的な分類、または前記イベントと関連付けられた前記意味論的な分類のうちの1つまたは複数に対する更新を含む請求項1に記載の方法。 - 1つまたは複数のプロセッサと、
メモリであって、前記1つまたは複数のプロセッサによって実行可能なプランナモジュールおよび第1の動作基準が前記メモリ上に記憶されており、それらが前記1つまたは複数のプロセッサによって実行されると、システムを、
自律車両の動作に関係付けられるセンサデータを取得することと、
少なくとも前記センサデータおよび前記第1の動作基準に基づいて、前記自律車両の動作のための第1の軌道を判定することと、
前記自律車両の動作のための第2の軌道を実施するための命令を受信することと、
第1の動作データに置き換えるための第2の動作データを生成することであり、前記第2の動作データは、前記1つまたは複数のプロセッサを、少なくとも前記センサデータおよび第2の動作基準に基づいて前記第2の軌道を判定するように構成する、ことと
を含む動作を実施するように構成する、メモリと
を備えたシステム。 - 前記動作基準は、
前記自律車両を動作させるための候補軌道を選択するための基準、
軌道の生成に対する制約を規定する規則、
前記自律車両の動作が規範的であるか否かを判定するための閾値信頼水準、
前記センサデータから、前記自律車両が動作している環境内のオブジェクトを検出するための分類子、
前記センサデータから知覚エンジンによって検出されるオブジェクトの意味論的な分類、
イベントと関連付けられた意味論的な分類、
1つまたは複数の候補軌道、または
前記候補軌道と関連付けられた信頼水準、もしくは、前記候補軌道と関連付けられた信頼水準を決定するための規則
のうちの1つまたは複数を含み、
前記更新された動作基準は、
候補軌道を選択するための前記基準、
軌道の生成に対する制約を規定する前記規則、
前記閾値信頼水準、
前記知覚エンジンの構成、
前記意味論的な分類、
前記候補軌道、
前記信頼水準、または
信頼水準を決定するための前記規則
のうちの1つまたは複数の修正またはそれらに対する追加を含む請求項15に記載のシステム。
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US11061398B2 (en) | 2015-11-04 | 2021-07-13 | Zoox, Inc. | Machine-learning systems and techniques to optimize teleoperation and/or planner decisions |
US11106218B2 (en) | 2015-11-04 | 2021-08-31 | Zoox, Inc. | Adaptive mapping to navigate autonomous vehicles responsive to physical environment changes |
US11283877B2 (en) | 2015-11-04 | 2022-03-22 | Zoox, Inc. | Software application and logic to modify configuration of an autonomous vehicle |
US11301767B2 (en) | 2015-11-04 | 2022-04-12 | Zoox, Inc. | Automated extraction of semantic information to enhance incremental mapping modifications for robotic vehicles |
US11314249B2 (en) | 2015-11-04 | 2022-04-26 | Zoox, Inc. | Teleoperation system and method for trajectory modification of autonomous vehicles |
US11796998B2 (en) | 2015-11-04 | 2023-10-24 | Zoox, Inc. | Autonomous vehicle fleet service and system |
US10962650B2 (en) | 2017-10-31 | 2021-03-30 | United States Of America As Represented By The Administrator Of Nasa | Polyhedral geofences |
JP2022528640A (ja) * | 2019-03-28 | 2022-06-15 | ニッサン ノース アメリカ,インク | 例外処理のための遠隔操作 |
JP7335350B2 (ja) | 2019-03-28 | 2023-08-29 | ニッサン ノース アメリカ,インク | 例外処理のための遠隔操作 |
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US20180329411A1 (en) | 2018-11-15 |
WO2017079474A2 (en) | 2017-05-11 |
WO2017079474A3 (en) | 2017-06-08 |
EP3371660A4 (en) | 2019-05-08 |
US10048683B2 (en) | 2018-08-14 |
US20170123419A1 (en) | 2017-05-04 |
US20190361432A1 (en) | 2019-11-28 |
EP3371660A2 (en) | 2018-09-12 |
US10591910B2 (en) | 2020-03-17 |
CN108292134B (zh) | 2022-08-16 |
US20180136644A1 (en) | 2018-05-17 |
US11061398B2 (en) | 2021-07-13 |
CN108292134A (zh) | 2018-07-17 |
JP7103946B2 (ja) | 2022-07-20 |
US9632502B1 (en) | 2017-04-25 |
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