- **ECAN:** Path Planning in 2D and 3D-environments using Convex-Quadratic Constrained Quadratic Program (QCQP); Semi-Definite Programming (SDP); and Second Order Cone Programming (SOCP), (Published)

- **R-ECAN:** Reinforced-ECAN; Submitted in IROS-2012 (a sample run is shown in the left figure).

- Absolute zero prior knowledge of the environment or the obstacles – they are discovered online.
- Due to convex formulation of the entire framework, solution is guaranteed at each time-step.
- No assumptions on shape of the agent: Agent can be convex or non-convex shaped - the algorithm uses Second Order Cone Programming to handle non-convex shaped agent (figure on the left)
- Uses point-cloud representation of obstacles discovered in the field-of-view during navigation: Exact boundary detection is not assumed

A path planning algorithm for planning online in completely unknown and unseen environments, with limited visibility, using convex optimization and reinforcement learning.

The project Convex-Reinforced Planning (CRP) is divided into two parts: (i) ECAN and (ii) R-ECAN. The first part focussed on inventing a convex optimization based path planner named ECAN. The second part focuses on incorporating reinforcement learning as a guidance mechanism to devise a robust planner R-ECAN. The R-ECAN resulted into the DFRL-E or the AWSF framework, which has the capability of generalizing any existing path or motion planner, and performing beyond the capabilities of the planners.

- Sanjeev Sharma,
*QCQP-Tunneling: Ellipsoidal Constrained Agent Navigation**.*In Proceedings of Second IASTED International Conference on Robotics (Robo), Nov 7-9, 2011, Pittsburgh, USA. - Sanjeev Sharma and Matthew E. Taylor,
*Autonomous Waypoint Generation Strategy for On-Line Navigation in Unknown Environments**.*In Proceedings of IROS Workshop on Robot Motion Planning: Online Reactive and in Real-Time, 2012, Portugal.

- My first presentation for this project during February 2010:

Video Presentation - ECAN, pdf - ECAN_CRP

- Path Planning channel of Searching:

Here you will find two presentations, one on ECAN and one explaining the MINIMUM VOLUME ELLIPSOIDS.

Path Planning Channel

- Link for all channels of searching-eye: Channels-SE

- See the work of George Konidaris on Skill Learning.

An approach to CRP: Convex-Reinforcement-Paths and Autonomous Path Planning.