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Falsification of Autonomous Systems in Rich Environments
Khen Elimelech, Morteza Lahijanian, Lydia E. Kavraki +1
Validating the behavior of autonomous Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) agents, which rely on automated controllers, is an objective of great importance…
Efficient Multi-Robot Motion Planning for Manifold-Constrained Manipulators by Randomized Scheduling and Informed Path Generation
Weihang Guo, Zachary Kingston, Kaiyu Hang +1
Multi-robot motion planning for high degree-of-freedom manipulators in shared, constrained, and narrow spaces is a complex problem and essential for many scenarios such as construc…
Scaling Long-Horizon Online POMDP Planning via Rapid State Space Sampling
Yuanchu Liang, Edward Kim, Wil Thomason +3
Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalabil…
Nearest-Neighbourless Asymptotically Optimal Motion Planning with Fully Connected Informed Trees (FCIT*)
Tyler S. Wilson, Wil Thomason, Zachary Kingston +2
Improving the performance of motion planning algorithms for high-degree-of-freedom robots usually requires reducing the cost or frequency of computationally expensive operations. T…
CaStL: Constraints as Specifications through LLM Translation for Long-Horizon Task and Motion Planning
Weihang Guo, Zachary Kingston, Lydia E. Kavraki
Large Language Models (LLMs) have demonstrated remarkable ability in long-horizon Task and Motion Planning (TAMP) by translating clear and straightforward natural language problems…
Object-Centric Kinodynamic Planning for Nonprehensile Robot Rearrangement Manipulation
Kejia Ren, Gaotian Wang, Andrew S. Morgan +2
Nonprehensile actions such as pushing are crucial for addressing multi-object rearrangement problems. Many traditional methods generate robot-centric actions, which differ from int…
Encoding Reusable Multi-Robot Planning Strategies as Abstract Hypergraphs
Khen Elimelech, James Motes, Marco Morales +3
Multi-Robot Task Planning (MR-TP) is the search for a discrete-action plan a team of robots should take to complete a task. The complexity of such problems scales exponentially wit…
Task and Motion Planning for Execution in the Real
Tianyang Pan, Rahul Shome, Lydia E. Kavraki
Task and motion planning represents a powerful set of hybrid planning methods that combine reasoning over discrete task domains and continuous motion generation. Traditional reason…
Collision-Affording Point Trees: SIMD-Amenable Nearest Neighbors for Fast Collision Checking
Clayton W. Ramsey, Zachary Kingston, Wil Thomason +1
Motion planning against sensor data is often a critical bottleneck in real-time robot control. For sampling-based motion planners, which are effective for high-dimensional systems…
Stochastic Games for Interactive Manipulation Domains
Karan Muvvala, Andrew M. Wells, Morteza Lahijanian +2
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…