tailieunhanh - Field and Service Robotics- Recent Advances - Yuta S. et al (Eds) Part 2

Tham khảo tài liệu 'field and service robotics- recent advances - yuta s. et al (eds) part 2', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Mobile Robots Facing the Real World 23 in our Lab that leads to locomotion concepts that perform extremely well in rough terrain still being efficient and not very complex fig. 5 and 6 . Environment Representation Environment perception and representation can be model- or behavior-based and might involve different levels of abstraction fig. 2 . Whereas behavior-based approaches are often combined with bio-inspired algorithms for adaptation and Fig. 2. This figure depicts the hierarchy of abstraction levels. More we go up in the hierarchy more we reduce the geometric information and more we increase the distinctiveness. For global localization and mapping high distinctiveness is of importance whereas for local action precise geometric relations with the environment come forward. Fig. 3. 3D representation of an indoor environment by planes. The raw data left are registered with an upward looking SICK laser scanner whereas a horizontally arranged laser scanner is used for probabilistic localization of the robot during the measurement. Through the extraction of plans right from the 13157 raw data points the representation can drastically be simplified to 27 planar regions thus reducing memory requirement and complexity 15 and filtering unimportant information. 24 R. Siegwart learning they hardly scale with more complex task and have only shown their feasibility in simple experiments. Model based approaches make use of a priory knowledge by means of environment models thus allow a very compact and taskdependant environment interpretation. They scale much better with the complexity of the system and task but have some limitations with highly nonlinear systems and unmodeled environment features. However today only model based control approaches enable predictivity of the systems behavior thus guaranteeing safety. Models can have different level of abstraction from raw-data based grid representations up to highly symbolic descriptions of the environment fig. 2 . For .