Search

Detection of chemical trails has multiple applications in industry and exploration, where prompt localization of dangerous substances encourages development of robust sensors, systems, and algorithms. Current chemical sensing robotics has focused on autonomous navigation, while transduction of chemical information to visual, tactile, or other types of sensory cues have not been thoroughly addressed. This work proposes the inclusion of a human operator in order to solve the robot navigation problem and proposes visual and haptic feedback arrangements that carry the information transmitted by the chemical sensors. A chemical source is placed in a simulated environment, which is navigated by a tracked robot controlled by human drivers. A multipoint haptic interface operates as the robot controller and provides force feedback according to the direction of the chemical gradient detected by the robot. Seven experiments test the tracking performance of three combinations of haptic and visual feedback under different air current configurations, which consistently prove the feasibility of a chemotaxis-based navigation system. Moreover, this work demonstrates with statistical significance that gradient information transmitted using haptic feedback minimizes the required time for reaching the chemical source. This enables the operator's visual capability in other important tasks during navigation (i.e., obstacle avoidance).

Fundamental dynamic programming recursive equations are extended to the multicriteria framework. In particular, a more detailed procedure for a general recursive solution scheme for the multicriteria discrete mathematical programming problem is developed. Definitions of lower and upper bounds are offered for the multicriteria case and are incorporated into the recursive equations to aid problem solution by eliminating inefficient subpolicies. Computational results are reported for a set of 0–1 integer linear programming problems.