TY - GEN
T1 - Coordinate Invariant User-Guided Constrained Path Planning with Reactive Rapidly Expanding Plane-Oriented Escaping Trees
AU - Laha, Riddhiman
AU - Sun, Ruiai
AU - Wu, Wenxi
AU - Mahalingam, Dasharadhan
AU - Chakraborty, Nilanjan
AU - Figueredo, Luis F.C.
AU - Haddadin, Sami
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As collaborative robots move closer to human environments, motion generation and reactive planning strategies that allow for elaborate task execution with minimal easy-to-implement guidance whilst coping with changes in the environment is of paramount importance. In this paper, we present a novel approach for generating real-time motion plans for point-to-point tasks using a single successful human demonstration. Our approach is based on screw linear interpolation, which allows us to respect the underlying geometric constraints that characterize the task and are implicitly present in the demonstration. We also integrate an original reactive collision avoidance approach with our planner. We present extensive experimental results to demonstrate that with our approach, by using a single demonstration of moving one block, we can generate motion plans for complex tasks like stacking multiple blocks (in a dynamic environment). Analogous generalization abilities are also shown for tasks like pouring and loading shelves. For the pouring task, we also show that a demonstration given for one-armed pouring can be used for planning pouring with a dual-armed manipulator of different kinematic structure.
AB - As collaborative robots move closer to human environments, motion generation and reactive planning strategies that allow for elaborate task execution with minimal easy-to-implement guidance whilst coping with changes in the environment is of paramount importance. In this paper, we present a novel approach for generating real-time motion plans for point-to-point tasks using a single successful human demonstration. Our approach is based on screw linear interpolation, which allows us to respect the underlying geometric constraints that characterize the task and are implicitly present in the demonstration. We also integrate an original reactive collision avoidance approach with our planner. We present extensive experimental results to demonstrate that with our approach, by using a single demonstration of moving one block, we can generate motion plans for complex tasks like stacking multiple blocks (in a dynamic environment). Analogous generalization abilities are also shown for tasks like pouring and loading shelves. For the pouring task, we also show that a demonstration given for one-armed pouring can be used for planning pouring with a dual-armed manipulator of different kinematic structure.
UR - https://www.scopus.com/pages/publications/85136325188
U2 - 10.1109/ICRA46639.2022.9812014
DO - 10.1109/ICRA46639.2022.9812014
M3 - Conference contribution
AN - SCOPUS:85136325188
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 977
EP - 984
BT - 2022 IEEE International Conference on Robotics and Automation, ICRA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Conference on Robotics and Automation, ICRA 2022
Y2 - 23 May 2022 through 27 May 2022
ER -