Adaptive Task and Motion Planning Strategies for Complex Tasks

EasyChair Preprint no. 12325

Abstract

This abstract explores the advancements and challenges in developing ATMP strategies to enhance the adaptability and efficiency of autonomous systems when faced with complex tasks. Traditional task and motion planning approaches often struggle to adapt to changing environments and task requirements, leading to suboptimal performance. However, recent research focuses on developing ATMP strategies capable of dynamically adjusting plans based on real-time feedback and environmental changes. Key advancements include the development of adaptive planning frameworks that leverage online replanning algorithms to adjust task and motion plans in response to unforeseen events or deviations from the initial plan. These frameworks enable autonomous systems to continuously assess their surroundings, anticipate potential obstacles, and modify their plans accordingly to achieve task objectives efficiently.

Keyphrases: motion, planning, strategies

@Booklet{EasyChair:12325,
  author = {Julia Anderson and Jhon Nick},
  title = {Adaptive Task and Motion Planning Strategies for Complex Tasks},
  howpublished = {EasyChair Preprint no. 12325},

  year = {EasyChair, 2024}}