The Patrolling Problem is a crucial feature of the surveillance task in defense and other establishments. Most of the works in the literature concentrate on reducing the Idleness value at each location in the environment. However, there are often a few prioritized locations that cannot be left unvisited beyond a certain Time Period. In this paper, we study the problem of Prioritized patrolling - the task of patrolling the given environment using multiple agents while ensuring the prioritized locations are visited within the pre-specified Time Period. We present a novel algorithm, namely, Time Period Based Patrolling (TPBP) algorithm, to solve the prioritized patrolling problem. It determines a sequence of walks for each agent online that complies with the Time Period requirement of the Priority nodes while reducing the Idleness of all the other nodes. We have tested and validated the algorithm using SUMO - a realistic simulator developed for traffic management. Since the existing strategies are not designed for Prioritized Patrolling, we show through comparison that proposed algorithm is required to solve the problem.

Path planning of a tool in Minimally Invasive Surgery (MIS) can provide assistance to the surgeons by giving solutions for faster and safe tool movements during the surgery. However, the main challenge in this problem is to address non-uniform tool shape for planning that can change due to the tool’s dexterity. A typical robotic path planning approach by describing the robot’s feasible movements using C-space is applied in this work. Unlike the robotic path planning problem, the C-space description capturing the movement does not give any closed-form solution due to high degree of freedom associated with the tool moved by human hands. Hence, an interval-based approach is used for describing the C-space. The proposed interval-based approach is capable of dividing the space into feasible and non-feasible intervals of different sizes which helps to reduce the search area and cover the obstacles in a refined manner. This paper presents collision-free and fast path computation using interval arithmetic between any two points in a 2D- surgical environment cluttered with obstacles for a surgical tool robot.

In this paper, an equivalent output injection based sliding mode observer is proposed for estimating the states of a class of perturbed n-dimensional nonholonomic systems. In the proposed design, we introduce a new transformation based on state scaling which renders the perturbed system in a triangular input form, amenable for the design of the observer. Thereafter, the equivalent control method is adopted in a sequential manner to estimate each of the system states one after another, in finite time such that ultimately all the states are estimated. Thus the entire state estimates are available for feedback after a finite time, in the presence of structured perturbations affecting the system. Simulations are performed on a unicycle mobile robot, to demonstrate the effectiveness of the proposed observer design.

This paper proposes a trajectory planning strategy to simultaneously address multiple surveillance objectives such as complete area coverage, periodic surveillance, and guaranteed detection of a rogue element attempting to exit the area of interest. For agents with identical sensing capability, the proposed strategy defines a time-varying multi-agent formation on a Lissajous curve, which completes the aforementioned tasks in finite time with collision free paths for all agents in a 2-D rectangular region. This obviates the need for sensing and communication for collision avoidance among agents. A sufficient upper limit on agent dimensions that ensures collision free motion is derived. An algorithm is developed for choosing the number of agents and optimal Lissajous curve for a prescribed rectangle and agents' sensing capability. The optimal Lissajous curve is chosen to minimize the time period for repeated coverage and maximize the upper bound on agent size. The proposed algorithm is validated through computer simulations and experiments using differential drive robots.

This paper considers the problem of generating a map of an indoor environment by a mobile robot when constraints are placed on sensing and processing hardware. In particular, we present an algorithm for Voronoi diagram generation by a mobile robot equipped merely with inexpensive ultrasonic sensors and a low-end Field Programmable Gate Array (FPGA) device. The algorithm is based on the definition of the Voronoi diagram in terms of the perpendicular-bisector. Deviations from the Voronoi diagram of the (reference) point on the robot are corrected by a novel algorithm that is devoid of division and floating-point operations. An efficient architecture and experiments with an FPGA-based robot are also presented.