← Search

Andrew M. Wells

7 accepted papers

2024

Stochastic Games for Interactive Manipulation Domains

ICRA 2024poster

As robots become more prevalent, the complexity of robot-robot, robot-human, and robot-environment interactions increases. In these interactions, a robot needs to consider not only the effects of its own actions, but also the effects of other agents’ actions and the possible interactions between age…

Cited by 1SourceScholar
2022

Failure is an option: Task and Motion Planning with Failing Executions

ICRA 2022poster

Future robotic deployments will require robots to be able to repeatedly solve a variety of tasks in application domains. Task and motion planning addresses complex robotic problems that combine discrete reasoning over states and actions and geometric interactions during action executions. Moving bey…

Cited by 10SourceScholar
2021

A General Task and Motion Planning Framework For Multiple Manipulators

IROS 2021poster

Many manipulation tasks combine high-level discrete planning over actions with low-level motion planning over continuous robot motions. Task and motion planning (TMP) provides a powerful general framework to combine discrete and geometric reasoning, and solvers have been previously proposed for sing…

Cited by 31SourceScholar
2020

Augmenting Control Policies with Motion Planning for Robust and Safe Multi-robot Navigation

IROS 2020poster

This work proposes a novel method of incorporating calls to a motion planner inside a potential field control policy for safe multi-robot navigation with uncertain dynamics. The proposed framework can handle more general scenes than the control policy and has low computational costs. Our work is rob…

Cited by 7SourceScholar
2020

Informing Multi-Modal Planning with Synergistic Discrete Leads

ICRA 2020poster

Robotic manipulation problems are inherently continuous, but typically have underlying discrete structure, e.g., whether or not an object is grasped. This means many problems are multi-modal and in particular have a continuous infinity of modes. For example, in a pick-and-place manipulation domain,…

Cited by 32SourceScholar
2019

Efficient Symbolic Reactive Synthesis for Finite-Horizon Tasks

ICRA 2019poster

When humans and robots perform complex tasks together, the robot must have a strategy to choose its actions based on observed human behavior. One well-studied approach for finding such strategies is reactive synthesis. Existing approaches for finite-horizon tasks have used an explicit state approach…

Cited by 47SourceScholar
2019

Learning Feasibility for Task and Motion Planning in Tabletop Environments

RA-L 2019

Task and motion planning (TMP) combines discrete search and continuous motion planning. Earlier work has shown that to efficiently find a task-motion plan, the discrete search can leverage information about the continuous geometry. However, incorporating continuous elements into discrete planners pr

Cited by 90SourceScholar