TAPIR: Toolkit for approximating and Adapting POMDP solutions In Real time
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.
For bug reports and other feedback, please e-mail us at firstname.lastname@example.org.
Videos (TAPIR with ROS+V-REP Interface)
A video demonstration of TAPIR. This video consists of two segments.
Release 0.3.1.b (23 September 2015)
- (0.3.1.b) Minor fixed on the default configuration of the problems.
- (0.3.1) Fixed compilation for ROS (added missing GPS-ABT source files to CMakeLists.txt).
- Added GPS-ABT for continuous action spaces.
- Added a ”–no-load” option to ./simulate so that it can be run without a need for serializing policies.
Release 0.2 (1 December 2014)
Release 0.1 (13 July 2014)
- Hanna Kurniawati (research group leader)
- Dimitri Klimenko (developed the core TAPIR library)
- Joshua Mun Song (developed the ROS + V-REP interface)
- Konstantin Seiler (adapted TAPIR for continuous action spaces)
- Vinay Yadav (helped to develop the basic ABT algorithm)