Active learning in robotics: A review of control principles
Active learning is a decision-making process. In both abstract and physical settings, active
learning demands both analysis and action. This is a review of active learning in robotics …
learning demands both analysis and action. This is a review of active learning in robotics …
Time optimal ergodic search
Robots with the ability to balance time against the thoroughness of search have the potential
to provide time-critical assistance in applications such as search and rescue. Current …
to provide time-critical assistance in applications such as search and rescue. Current …
Asymmetric self-play-enabled intelligent heterogeneous multirobot catching system using deep multiagent reinforcement learning
Aiming to develop a more robust and intelligent heterogeneous system for adversarial
catching in security and rescue tasks, in this article, we discuss the specialities of applying …
catching in security and rescue tasks, in this article, we discuss the specialities of applying …
Decision-Theoretic Approaches for Robotic Environmental Monitoring--A Survey
Robotics has dramatically increased our ability to gather data about our environments. This
is an opportune time for the robotics and algorithms community to come together to …
is an opportune time for the robotics and algorithms community to come together to …
A pareto-optimal local optimization framework for multiobjective ergodic search
Our work is motivated by humanitarian assistant and disaster relief (HADR) where often it is
critical to find signs of life in the presence of conflicting criteria, objectives, and information …
critical to find signs of life in the presence of conflicting criteria, objectives, and information …
Safety-critical ergodic exploration in cluttered environments via control barrier functions
In this paper, we address the problem of safe trajectory planning for autonomous search and
exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) …
exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) …
An ergodic measure for active learning from equilibrium
This article develops KL-ergodic exploration from equilibrium (KL-E 3), a method for robotic
systems to integrate stability into actively generating informative measurements through …
systems to integrate stability into actively generating informative measurements through …
Tuning movement for sensing in an uncertain world
While animals track or search for targets, sensory organs make small unexplained
movements on top of the primary task-related motions. While multiple theories for these …
movements on top of the primary task-related motions. While multiple theories for these …
Fast ergodic search with kernel functions
Ergodic search enables optimal exploration of an information distribution while
guaranteeing the asymptotic coverage of the search space. However, current methods …
guaranteeing the asymptotic coverage of the search space. However, current methods …
A Survey of Decision-Theoretic Approaches for Robotic Environmental Monitoring
Robotics has dramatically increased our ability to gather data about our environments,
creating an opportunity for the robotics and algorithms communities to collaborate on novel …
creating an opportunity for the robotics and algorithms communities to collaborate on novel …