人民大学蓝虹谈以生态信用支持海洋保护
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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好好 学习了 确实不错
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