Obstacle detection and mapping in low-cost, low-power multi-robot systems using an Inverted Particle Filter

Adam Leon Kleppe (1) , Amund Skavhaug (1)

1 ITK NTNU - Department of Engineering Cybernetics [Trondheim]

There are a vast number of methods for detecting obstacles, though not taking resource consumption into consideration. The proposed method is an obstacle detection and mapping method focused on systems with constrained memory capacity and processing power, and is called the Inverted Particle Filter. This method has small resource requirements, and can be fine tuned according to available resources. The conducted experiments show promising results.

Mots clés: Safety; Embedded systems; computational power; low-cost; low-energy; power consumption; obstacle detection; mapping

Domaines: Systèmes embarqués

Adam Leon Kleppe, Amund Skavhaug. Obstacle detection and mapping in low-cost, low-power multi-robot systems using an Inverted Particle Filter. SAFECOMP 2013 - Workshop DECS (ERCIM/EWICS Workshop on Dependable Embedded and Cyber-physical Systems) of the 32nd International Conference on Computer Safety, Reliability and Security, Sep 2013, Toulouse, France. pp.NA. ⟨hal-00849817⟩