Path Planning Method for UUV Homing and Docking in Movement Disorders Environment

Algorithm 1

Step  1. Initial.

  Substep 1. Set the initial parameters: n, M, 𝜔^𝑡_𝑖, 𝑐_max, 𝑐_min

  Substep 2. Random initial 𝑥^𝑡_𝑖𝑑(0)

  Substep 3. Random initial 𝑣^𝑡_𝑖𝑑(1)

  Substep 4. Calculate fitness𝑥^𝑡_𝑖(0) and set 𝑝^𝑡_𝑖(0)=𝑥^𝑡_𝑖(0), 𝑝^𝑡_𝑢(0)=min𝑝^𝑡₁(0),𝑝^𝑡₂(0)

  Substep 5. 𝑝_𝑔(0)=𝑥^𝑡_𝑖(0)∣𝑥^𝑡_𝑖(0)∈minfitness𝑥^𝑡_𝑖(0)

Step  2. If the criteria are satisfied, output the best solution; otherwise, go to Substep 6.

  Substep 6. Update 𝑣^𝑡_𝑖𝑑(𝑘),

       𝑣^𝑡_1𝑑(𝑘+1)=𝜔^𝑡₁𝑣_1𝑑(𝑘)+𝑐_max𝑟^𝑡₁𝑝^𝑡_1𝑑(𝑘)−𝑥^𝑡_1𝑑(𝑘)+𝑐_min𝑟^𝑡₂𝑝_𝑔𝑑(𝑘)−𝑥^𝑡_1𝑑(𝑘);

       if 𝑝^𝑡_𝑢𝑑(𝑘)≥𝑝^𝑡_𝑢𝑑(𝑘−1)

           𝑣^𝑡_2𝑑(𝑘+1)=𝜔^𝑡₂𝑣_2𝑑(𝑘)+𝑐_min𝑟^𝑡₃𝑝^𝑡_𝑢𝑑(𝑘)−𝑥^𝑡_2𝑑(𝑘)+𝑐_max𝑟^𝑡₄𝑝_𝑔𝑑(𝑘)−𝑥^𝑡_2𝑑(𝑘);

       else

           𝑣^𝑡_2𝑑(𝑘+1)=0;

  Substep 7. Update 𝑥^𝑡_𝑖𝑑(𝑘),

        𝑥^𝑡_1𝑑(𝑘+1)=𝑥^𝑡_1𝑑(𝑘)+𝑣^𝑡_1𝑑(𝑘+1);

       if 𝑝^𝑡_𝑢𝑑(𝑘)≥𝑝^𝑡_𝑢𝑑(𝑘−1)

        𝑥^𝑡_2𝑑(𝑘+1)=𝑥^𝑡_2𝑑(𝑘)+𝑣^𝑡_2𝑑(𝑘+1);

       else

        𝑥^𝑡_2𝑑(𝑘+1)=𝑝^𝑡_𝑢𝑑(𝑘);

  Substep 8. Calculate fitness𝑥^𝑡_𝑖(𝑘)

  Substep 9. if fitness𝑥^𝑡_𝑖(𝑘)<fitness𝑝^𝑡_𝑖(𝑘)

           𝑝^𝑡_𝑖(𝑘)=𝑥^𝑡_𝑖(𝑘);

       if 𝑝^𝑡₁(𝑘)<𝑝^𝑡₂(𝑘)

           𝑝^𝑡_𝑢(𝑘)=𝑝^𝑡₁(𝑘);

       else

           𝑝^𝑡_𝑢(𝑘)=𝑝^𝑡₂(𝑘);

       if minfitness𝑥^𝑡_𝑖(𝑘),𝑖=1,2,𝑡=1,…,𝑛/2<fitness𝑝_𝑔(𝑘)

           𝑝_𝑔(𝑘)=𝑥^𝑡_𝑖(𝑘)|minfitness𝑥^𝑡_𝑖(𝑘),𝑖=1,2,𝑡=1,…,𝑛/2;

  Substep 10. Go back to Step   2.