The optimal traverse of irregular terrains made by ground mobile robots heavily depends on the adequacy of the cost models used to plan the path they follow. The criteria to define optimality may be based on minimizing energy consumption and/or preserving the robot stability. This entails the proper assessment of anisotropy to account for the robot driving on top of slopes with different directions. To fulfill this demand, this paper presents the Continuous Anisotropic Model for Inclined Surfaces, a cost model compatible with anisotropic path planners like the bi-directional Ordered Upwind Method. This model acknowledges how the orientation of the robot with respect to any slope determines its energetic cost, considering the action of gravity and terramechanic effects such as the slippage. Moreover, the proposed model can be tuned to define a trade-off between energy minimization and Roll angle reduction. The results from two simulation tests demonstrate how, to find the optimal path in scenarios containing slopes, in certain situations the use of this model can be more advantageous than relying on isotropic cost functions. Finally, the outcome of a field experiment involving a skid-steering robot that drives on top of a real slope is also discussed.
RIT*: Riemannian Informed Trees for Cost-Adaptive Optimal Motion Planning
Center for Autonomous Robotic Systems, Khalifa University（哈利法大学自主机器人系统中心）；Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya（加泰罗尼亚理工大学工业与控制工程研究所）
Robust Maneuver Planning With Scalable Prediction Horizons: A Move Blocking Approach
Institute of Flight Systems, German Aerospace Center (DLR)（德国航空航天中心飞行系统研究所）；Institute for Production Technology and Systems, Leuphana University of Lueneburg（吕讷堡勒法纳大学生产技术与系统研究所）
Coverage Path Planning for Autonomous Sailboats in Inhomogeneous and Time-Varying Oceans: A Spatiotemporal Optimization Approach
Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences（中国科学院深海科学与工程研究所）；Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院海洋工程研究所）；ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University（浙江大学 Hangzhou 全球科技创新中心）；Department of Engineering, Faculty of Computing, Engineering and the Built Environment, Birmingham City University（伯明翰城市大学工程系）；School of Ocean and Civil Engineering, Shanghai Jiao Tong University（上海交通大学海洋与Civil Engineering学院）
