This　paper　presents　a　robust　computationally　efficient　real-time　collision　avoidance　algorithm　for　Unmanned　Aerial　Vehicle　(UAV),　namely　Memory-based　Wall　Following-Artificial　Potential　Field　(MWF-APF)　method.　The　new　algorithm　switches　between　Wall-Following　Method　(WFM)　and　Artificial　Potential　Field　method　(APF)　with　improved　situation　awareness　capability.　Historical　trajectory　is　taken　into　account　to　avoid　repetitive　wrong　decision.　Furthermore,　it　can　be　effectively　applied　to　platform　with　low　computing　capability.　As　an　example,　a　quad-rotor　equipped　with　limited　number　of　Time-of-Flight　(TOF)　rangefinders　is　adopted　to　validate　the　effectiveness　and　efficiency　of　this　algorithm.　Both　software　simulation　and　physical　flight　test　have　been　conducted　to　demonstrate　the　capability　of　the　MWF-APF　method　in　complex　scenarios.　©　2018　IEEE.