Vídeo: Robotics & Artificial Intelligence Lab
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TecnologíaTranscripción
00:00This research proposes a hierarchical navigation module capable of high-speed legged locomotion
00:04even in complex and discreet terrain distribution environments
00:07and performing extreme parkour maneuvers such as running on walls or jumping over large gap.
00:16The proposed navigation module robustly operates in complex environments
00:21composed of various types of obstacles.
00:23We have structured the entire pipeline into three modules.
00:26The planner module, the tracker module, and the target updater.
00:30The planner module generates a feasible foothold from the map.
00:33The target updater changes the target foothold for the robot to step on.
00:37The tracker module controls the robot to accurately step on the given target foothold.
00:42We first trained the tracker module to achieve high performance during the training stage.
00:46The tracker module was trained using reinforcement learning on the Razum simulator.
00:50We employed a generative model called Map Generator, which evolves adversarially with the tracker module
00:55to provide desired difficulty environments.
00:56At deployment stage, we can observe the operation of each module on the real experiment.
01:02While the tracker module is operating, if the robot sufficiently steps on the target foothold,
01:06target updater updates the foothold target.
01:09When the front target is updated, it activates the planner module.
01:12The planner module runs simultaneously on a detached thread.
01:15While the tracker module controls the robot to precisely step on next target,
01:18planner module generates a feasible and safe foothold plan.
01:21To reduce time complexity in planning, the rear foot steps where the front foot has stepped.
01:26Planner draws multiple foothold samples through random sampling and rejects risky and difficult
01:31footholds using a consecutive filtering structures.
01:34Subsequently, the candidate foothold plans are evaluated through rollout in the physics simulation,
01:39and the one with the lowest cost is selected and provided to tracker as a next target.
01:43The planning module performs sampling and rollouts in parallel across eight different threads,
01:49separate from the tracker module.
01:51The real robot controlled by the tracker module is depicted in gray,
01:54while the rollout process is shown in blue.
01:57The final goal position is represented by a light green cube.
02:00The robust navigation module performs well even on maps with various unstructured obstacles.
02:09These maps include maps with pillars of various shapes and heights arranged sequentially,
02:13maps with impassable pillars or pits in discrete terrains,
02:16maps with 1.1-meter patches tilted randomly up to 30 degrees,
02:19maps with steps of varying heights and lengths,
02:22maps with consecutive ramp pillars of various heights and angles,
02:25and maps requiring descent or ascent of high ledges.
02:27The navigation module operates robustly even when the goal position is suddenly changed.
02:33It can traverse approximately 90 meters through maps with mixed obstacles
02:36at an average speed of 2.7 meter per second
02:39and maximum speed of 3.63 meter per second without a single failure.
02:43This experiment demonstrates the powerful performance of the tracker module,
02:47a map requiring ascent and descent of 0.6 meter obstacle,
02:52a map requiring side flutter,
02:54a map requiring jump-across-gap up to 1.3 meters wide,
03:00a map requiring traversal of double ramps facing in opposite directions,
03:10a map consisting of triple consecutive ramps,
03:19a map requiring running on a single wall.
03:28The following video demonstrates the performance of the entire pipeline in a complex environment.
03:45The scenario involves a map with stairs and various obstacles,
03:48where the goal is positioned on the right.
03:50As before, the scenario involves a map with stairs and various obstacles,
04:00but this time the goal is positioned on the left.
04:02This scenario involves a map with various sized boxes and ramps,
04:17where the cost for avoiding height changes is low.
04:19This scenario involves a map with various sized boxes and ramps,
04:32where the cost for avoiding height changes is high.
04:34This scenario involves a map with boxes and slanted surfaces requiring abrupt directional changes,
04:53with gaps up to 1.3 meters wide.
04:55This scenario involves a map with boxes and slanted surfaces requiring abrupt directional changes,
04:56with gaps up to 1.3 meters wide.
04:59soilما above 2 Nevertheless,
05:01being made carefully around 3 e.8 meters wide and
05:14more powerful91 meters beyond the left to place.
05:18A map with facts,
05:21viaje to 2,0 meters wide and continue to form the dangers of a distributed position.