TAPIR is a C++ implementation of the Adaptive Belief Tree (ABT) algorithm. ABT is an online and anytime approximate POMDP solver capable of computing approximately optimal solution of various robotics problems, including robots operating in partially known and dynamic environments, in real-time.
TAPIR automatically updates the POMDP model as needed when the environment or the robot's understanding of its environment changes. It then adapts the POMDP solution to modifications of the POMDP model without the need to reconstruct the policy from scratch.
TAPIR provides a command-line interface, as well as an interface with ROS and V-REP.
TAPIR can be downloaded from our github repo.
Videos (TAPIR with ROS+V-REP Interface)
A video demonstration of TAPIR. This video consists of two segments. First is a Target Tracking scenario in continuous state space when the environment map is not known a priori. During runtime, the robot scans its environment, builds a map, updates the POMDP model, and adjusts the POMDP policy it uses. Second is Tag benchmark in larger environment, showing how TAPIR adjusts its policy in response to changes in the environment at runtime.
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