A mapping and/or localisation process including: (i) a pose optimisation process to optimise an approximate pose of a sensor with respect to an object using sensor data, the pose optimisation process comprising: receiving a model of an object including location information; receiving sensor data relating to at least part of the object, the sensor data being in a sensor frame of reference, the sensor data being associated with pose data representing a pose of a sensor used to generate the sensor data; projecting at least part of the model onto the sensor frame of reference; identifying corresponding feature points and/or feature lines between the model and sensor data in the sensor frame of reference; and optimising the pose data based on the identified correspondence, using a location difference in the corresponding feature points and/or feature lines between the model and the sensor data in the sensor frame of reference; and wherein: (ii) optimising at least one parameter of the model of the object, wherein the at least one parameter defines an estimated configuration of the object, and wherein optimising the at least one parameter includes optimising the at least one parameter based on the correspondence between the feature points and/or feature lines, and the optimised pose data, characterized in that the optimised parameter represents the configuration of the object, the configuration of the object including the relative position of parts of the object with respect to each other, wherein the parts of the object are moveable with respect to each other. (i) a pose optimisation process to optimise an approximate pose of a sensor with respect to an object using sensor data, the pose optimisation process comprising: receiving a model of an object including location information; receiving sensor data relating to at least part of the object, the sensor data being in a sensor frame of reference, the sensor data being associated with pose data representing a pose of a sensor used to generate the sensor data; projecting at least part of the model onto the sensor frame of reference; identifying corresponding feature points and/or feature lines between the model and sensor data in the sensor frame of reference; and optimising the pose data based on the identified correspondence, using a location difference in the corresponding feature points and/or feature lines between the model and the sensor data in the sensor frame of reference; and wherein: receiving a model of an object including location information; receiving sensor data relating to at least part of the object, the sensor data being in a sensor frame of reference, the sensor data being associated with pose data representing a pose of a sensor used to generate the sensor data; projecting at least part of the model onto the sensor frame of reference; identifying corresponding feature points and/or feature lines between the model and sensor data in the sensor frame of reference; and optimising the pose data based on the identified correspondence, using a location difference in the corresponding feature points and/or feature lines between the model and the sensor data in the sensor frame of reference; and wherein: (ii) optimising at least one parameter of the model of the object, wherein the at least one parameter defines an estimated configuration of the object, and wherein optimising the at least one parameter includes optimising the at least one parameter based on the correspondence between the feature points and/or feature lines, and the optimised pose data, characterized in that the optimised parameter represents the configuration of the object, the configuration of the object including the relative position of parts of the object with respect to each other, wherein the parts of the object are moveable with respect to each other.