Multiobjective path planning on uneven terrains based on NAMOA

Nuwan Ganganath, Chi Tsun Cheng, Chi Kong Tse

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)


Existing path planning algorithms are capable of finding physically feasible, shortest, and energy-efficient paths for mobile robots navigating on uneven terrains. However, shortest paths on uneven terrains are often energy inefficient while energy-optimal paths usually take long time to be traversed. Therefore, due to time and energy constraints imposed on mobile robots, these shortest and energy-optimal paths might not be applicable. We propose a multiobjective path planner that can find pareto-optimal solutions in terms of path length and energy consumption. It is based on NAMOA - search algorithm that utilizes a proposed monotone heuristic cost function. The simulation results show that nondominated path options found by the proposed path planner can be very useful in many real-world applications.
Original languageEnglish
Title of host publicationISCAS 2016 - IEEE International Symposium on Circuits and Systems
Number of pages4
ISBN (Electronic)9781479953400
Publication statusPublished - 29 Jul 2016
Event2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016 - Montreal's Sheraton Centre, Montreal, Canada
Duration: 22 May 201625 May 2016


Conference2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016


  • heuristic search
  • Multiobjective
  • pareto-optimal
  • path planning
  • uneven terrains

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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