本研究以台灣建築外牆常見的窗簷、遮陽板或陽台欄杆等牆面凸起物為目標，設計可在這些凸塊抓握並進行壁面橫向移動的新型抓技機器人。我們根據體育競技選手在攀岩時的獨特運動方式設計機器人的運動模式並採用中樞模式產生器(CPG)實現機器人向右與向左橫向攀爬之運動控制。不同於既有文獻中使用CPG控制器進行機器人運動模式切換的狀況，本研究的應用場景在機器人切換攀爬步態過程中有可能會因某隻夾爪鬆開使其從壁面掉落，因此我們針對此問題加入限制條件以最佳化方式求得攀爬步態的CPG控制參數確保步態轉換時的強健性。為增強此橫向攀爬機器人對於戶外環境的適應能力，我們亦加入紅外線感測器偵測壁面凸起物之可能傾角，並採用夾爪姿態回授控制降低量測誤差。基於感測器量得之傾角資訊，我們以結合路徑規劃與CPG之運動控制策略使機器人能自主地即時調整自身運動姿態，順暢攀爬具傾角變化的壁面場景。本研究最後參考戶外實際壁面設計多組機器人攀爬實驗場景驗證本研究所提運動控制策略之可行性，實驗結果顯示機器人可成功完成水平與具傾角之場景往復攀爬動作。

Inspired by the commonly seen window eaves, balcony visors, and balcony balustrades in Taiwan’s buildings, this study aims to develop an innovative brachiation robot which can transversely move along these bulges on the wall. The robot is designed to mimic the unique locomotion styles performed by the players of sports competition shows and the central pattern generator (CPG) is particularly adopted to implement such transverse-climbing locomotion control. Because the discussed application scenario is different from the other existing CPG based locomotion switching scenarios, the robot’s grippers may become loose and cause the robot fall off from the hand-holding ledge during the course of locomotion transition. To address this robustness issue a set of optimal locomotion parameters in CPG controller is found by adding posture constraints to the formulated optimization problem. Four infrared sensors are installed on the robot to detect the inclined angles of the ledges on the wall and thus improve the robot’s adaptability to environmental changes. Gripper posture feedback control is also implemented associated with the whole CPG locomotion control system for reduced measurement noises. Based on the inclined angle information provided from the IR sensors, a locomotion control strategy integrated with path planning and CPG control is proposed with the goal of making the designed robot autonomously adjust the locomotion styles subject to the changes in inclined angles. A number of testing scenarios were set up to validate the feasibility of the proposed locomotion control strategy. The experimental results demonstrate that the developed robot can successfully finish the reciprocating transverse-climbing tasks containing both horizontal and inclined ledge scenarios.

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