10 accepted papers
The Dubins Moving Target Traveling Salesman Problem with Obstacles (Dubins MT-TSP-O) seeks an obstacle-free trajectory for an agent with a fixed speed and minimum turning radius that intercepts several moving targets. To tackle this NP-hard problem, we introduce the Lazy Iterated Random Generalized …
The moving target traveling salesman problem with obstacles (MT-TSP-O) seeks an obstacle-free trajectory for an agent that intercepts a given set of moving targets, each within specified time windows, and returns to the agent's starting position. Each target moves with a constant velocity within its
When agents must execute multiple tasks at spatially distinct locations, it is common to formulate and solve a Traveling Salesman Problem (TSP) to find the order of locations (targets) that requires the smallest travel cost. Approaching such task sequencing problems as a TSP is restrictive, as it re
Robotic search and rescue, exploration, and inspection require trajectory planning across a variety of domains. A popular approach to trajectory planning for these types of missions is ergodic search, which biases a trajectory to spend time in parts of the exploration domain that are believed to con
We develop a planner that directs robots to construct a 3D target structure composed of blocks. The robots themselves are cubes of the same size as the blocks, and they may place, carry, or remove one block at a time. When moving, robots are also allowed to climb or descend a block. A construction p…
Computing the distance from a point to a triangle mesh is a key computational step in robotics pipelines such as registration and collision detection, with applications to path planning, SLAM, and RGB-D vision. Numerous techniques to accelerate this computation have been developed, many of which use…
Consider a Multi-Agent Collective Construction (MACC) problem that aims to generate a plan for fictitious cubic robots to build a three-dimensional structure comprised of cubic blocks. These cubic robots can carry one cubic block at a time; robots may move left, right, forwards, backward, or climb u…
Search and rescue applications often need multiple agents to complete a set of conflicting tasks. This paper studies a Multi-Agent Multi-Objective Ergodic Search (MA-MO-ES) approach to this problem where each objective or task is to cover a domain subject to an information map. The goal is to alloca…
Expected value computations are a key bottleneck for path planning under uncertainty. Computing an expected value requires integrating over the uncertainty domain, which may be high dimensional. One way to accelerate such calculations is through the use of a “sparse” numerical integration scheme. Th
The use of motion primitives to plan trajectories has received significant attention in the robotics literature. This work considers the application of motion primitives to path planning and obstacle avoidance problems in which the system is subject to significant parametric and/or initial condition