Aiming　at　the　problems　of　smoothness　and　efficiency　in　current　path　planning　methods,　based　on　jump　point　search　(JPS),　a　path　planning　method　considering　both　smoothness　and　search　efficiency　was　proposed,　and　the　trajectory　was　optimized　by　polynomial.　Firstly,　in　order　to　improve　the　smoothness　of　the　path,　two　optimization　objectives　were　proposed　to　optimize　the　path　sequence,　that　was,　each　corner　of　the　path　was　on　the　vertex　of　the　obstacle　grid,　and　the　obstacles　that　contacted　with　the　path　corner　were　located　on　the　side　with　the　angle　less　than　180　degrees.　Then,　the　search　rules　of　JPS　were　improved　to　get　more　valuable　paths,　and　each　path　was　smoothed,　and　then　the　path　selection　was　made　by　weighing　the　length　and　angle　with　certain　rules.　Finally,　polynomial　was　used　to　optimize　the　path,　and　the　time　allocation　of　the　trajectory　optimization　method　was　studied　to　speed　up　the　iterative　efficiency.　The　feasibility　and　effectiveness　of　this　method　were　proved　by　simulation　and　comparison　with　other　algorithms.　The　results　showed　that　the　method　had　the　advantages　of　high　efficiency　of　JPS　algorithm,　and　effectively　solved　the　problems　of　redundant　points　and　frequent　turning　points　in　path　planning　of　JPS　algorithm.　In　different　density　environments,　compared　with　the　smoothed　JPS　algorithm,　the　path　planning　method　reduced　the　path　length　by　0.48%~1.80%,　and　the　cumulative　turning　angle　was　decreased　by　16.93%~52.75%.　In　the　large　environment,　the　proposed　method　had　similar　smoothness　to　Lazy-Theta*,　but　it　had　higher　search　efficiency.　The　cosine　function　was　used　to　allocate　time　to　accelerate　the　iterative　efficiency　of　trajectory　optimization,　and　good　results　were　obtained　through　experiments.　©　2021,　Chinese　Society　of　Agricultural　Machinery.　All　right　reserved.