人民大学蓝虹谈以生态信用支持海洋保护

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人民大学蓝虹谈以生态信用支持海洋保护

抓取基准让四种机器人实际执行候选动作

算法能提出许多抓取姿势，不代表机械臂都能到达那些位置。GraspBench在MuJoCo仿真环境中加入针对每种机器人的逆运动学筛选、运动规划以及接近、合拢、提起的执行步骤。团队用四种机器人、五类测试物体和一组桌面姿态评估六套方案，每套经历540个场景，合计3240次方法与场景组合测试。没有输出动作也计为失败。 Abdul Basit等人的这项研究收录在11月6日更新的计算机科学预印本列表中。

在固定场景中，GraspGen的总体成功率为73.1%，EconomicGrasp为63.5%。候选姿势最多的GPG最终成功率为44.3%。不同机器人本体和物体形状会改变结果，因而排名衡量的是从生成姿势到完成提起的整套配置。研究没有把同一场景下反复执行的随机波动纳入估计，这也是将结果推广到实际设备前需要区分的条件。

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