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Collision-Free Trajectory Planning with Deadlock Prevention: An Adaptive Virtual Target Approach
IEEE Access ( IF 3.4 ) Pub Date : 2020-01-01 , DOI: 10.1109/access.2020.3004205
Rishi Mohan , Emilia Silvas , Henry Stoutjesdijk , Herman Bruyninckx , Bram De Jager

Most human-centred robotic applications require robots to follow a certain pre-defined path. This makes the robot’s autonomous movements acceptable and predictable for humans. Planning a trajectory for the robot thus involves guiding it along this desired path. The classical approach of segmenting a path into multiple waypoints and tracking them only works well in environments which are obstacle-free or contain fixed stationary obstacles. Movable or dynamic obstacles that can potentially lie directly on waypoints result in deadlock situations causing the robot to oscillate around the desired waypoint without moving forward. This chapter presents a novel approach for trajectory planning in which an Adaptive Virtual Target (AVT) is formulated that follows the desired path irrespective of surrounding obstacles. The AVT essentially plays the role of a moving reference for the trajectory planner to track. Additionally, the AVT velocity can be adapted such that the robot can catch up in case of deviations from the path due to obstacle avoidance manoeuvres. A model predictive control (MPC) based trajectory planner tracks the AVT and accounts for obstacle avoidance. The proposed approach allows the robot to keep moving towards the goal by preventing deadlocks while simultaneously minimizing deviation from the desired path. Simulations based on a medical X-ray robot are provided to validate the approach.

中文翻译:

具有死锁预防的无碰撞轨迹规划:一种自适应虚拟目标方法

大多数以人为中心的机器人应用都要求机器人遵循特定的预定义路径。这使得机器人的自主运动对人类来说是可以接受和可预测的。因此,为机器人规划轨迹涉及沿着这条所需的路径引导它。将路径分割成多个航路点并跟踪它们的经典方法仅适用于无障碍物或包含固定静止障碍物的环境。可能直接位于航点上的可移动或动态障碍物会导致死锁情况,导致机器人在所需航点周围摆动而不向前移动。本章介绍了一种新的轨迹规划方法,其中制定了一个自适应虚拟目标 (AVT),该方法遵循所需的路径而不受周围障碍物的影响。AVT 本质上扮演着轨迹规划器跟踪的移动参考的角色。此外,可以调整 AVT 速度,以便机器人可以在由于避障操作而偏离路径的情况下追上。基于模型预测控制 (MPC) 的轨迹规划器跟踪 AVT 并考虑避障。所提出的方法允许机器人通过防止死锁同时最小化与所需路径的偏差来保持朝着目标移动。提供了基于医疗 X 射线机器人的模拟来验证该方法。基于模型预测控制 (MPC) 的轨迹规划器跟踪 AVT 并考虑避障。所提出的方法允许机器人通过防止死锁同时最小化与所需路径的偏差来保持朝着目标移动。提供了基于医疗 X 射线机器人的模拟来验证该方法。基于模型预测控制 (MPC) 的轨迹规划器跟踪 AVT 并考虑避障。所提出的方法允许机器人通过防止死锁同时最小化与所需路径的偏差来保持朝着目标移动。提供了基于医疗 X 射线机器人的模拟来验证该方法。
更新日期:2020-01-01
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